Vehicle vision system with lens pollution detection

Abstract

A vehicular vision system includes a camera and a processor operable to process captured image data. With the vehicle moving, the processor models outputs of photosensing elements of the camera as Gaussian distributions. With the vehicle moving, the processor determines an output of respective photosensing elements over multiple frames of captured image data, and determines whether the output of a photosensing element fits the Gaussian distribution for that element. Responsive to determination that the output of the element fits within the respective Gaussian distribution for that element, the system classifies that element as a blocked element. Responsive to determination that the output of the element does not fit within the respective Gaussian distribution for that element, the system classifies that element as a not blocked element. Responsive to determination that the ratio of blocked elements to not blocked elements is greater than a threshold ratio, a blockage condition is determined.

Description

FIELD OF THE INVENTION

The present invention relates to imaging systems or vision systems for vehicles.

BACKGROUND OF THE INVENTION

Use of imaging sensors in vehicle imaging systems is common and known. Examples of such known systems are described in U.S. Pat. Nos. 5,949,331; 5,670,935 and/or 5,550,677, which are hereby incorporated herein by reference in their entireties.

SUMMARY OF THE INVENTION

The present invention provides a vision system or imaging system for a vehicle that utilizes one or more cameras to capture images exterior of the vehicle, and provides the communication/data signals, including camera data or image data, that may be displayed at a display screen that is viewable by the driver of the vehicle, such as when the driver is backing up the vehicle, and that may be processed and, responsive to such image processing, the system may detect an object at or near the vehicle and in the path of travel of the vehicle, such as when the vehicle is backing up. The vision system is operable detect pollution or contaminants, such as water, mud, salt and/or the like, that is/are disposed at the lens or cover of the camera, and may generate an alert or may operate to clean or wipe the lens or cover in response to detection of a threshold degree of pollution or contaminants at or on the lens or cover.

According to an aspect of the present invention, a vision system for a vehicle includes at least one camera or image sensor disposed at a vehicle and having a field of view exterior of the vehicle, and a processor operable to process data transmitted by the camera. The vision system may be operable to compare contrast ratios of outputs of photosensing elements or pixels of the pixelated imaging array of the camera or imager to determine if some of the pixels are blocked by contaminants or the like at the lens of the camera, and/or the vision system may be operable to monitor pixels of the pixelated imaging array and, when the pixels fit a Gaussian distribution, the processor or system may classify the pixels as blocked pixels and, responsive to a determination that a number of blocked pixels is greater than a threshold level, the processor determines that there are contaminants at the lens of the camera. Responsive to the processor determining that there are contaminants at the lens of the camera, the system may generate an alert and/or adapt processing of image data to at least partially accommodate for the presence of the determined contaminants and/or clean the lens. The processor or algorithm may be incorporated in circuitry of the camera, or the processor or algorithm may be incorporated in circuitry of a control of the vehicle or a control of the vision system that is separate from the camera and camera circuitry.

These and other objects, advantages, purposes and features of the present invention will become apparent upon review of the following specification in conjunction with the drawings.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a plan view of a vehicle with a vision system and imaging sensors or cameras that provide exterior fields of view in accordance with the present invention;

FIG. 2 is a table of auto exposure (AE) zone labels for an exemplary imager for a vehicle vision system;

FIG. 3 is a table of AE zone brightness registers for an exemplary imager;

FIG. 4 is a flow chart of a pollution detection algorithm of the present invention;

FIG. 5 is an image captured by an imager showing an exemplary scene as processed by a pollution detection algorithm of the present invention; and

FIG. 6 is a flow chart of an ECU-based algorithm of the present invention.

DESCRIPTION OF THE PREFERRED EMBODIMENTS

A vehicle vision system and/or driver assist system and/or object detection system and/or alert system operates to capture images exterior of the vehicle and may process the captured image data to display images and to detect objects at or near the vehicle and in the predicted path of the vehicle, such as to assist a driver of the vehicle in maneuvering the vehicle in a rearward direction. The vision system includes a processor that is operable to receive image data from one or more cameras and may provide a displayed image that is representative of the subject vehicle (such as for a top down or bird's eye or surround view, such as discussed below).

Referring now to the drawings and the illustrative embodiments depicted therein, a vehicle 10 includes an imaging system or vision system 12 that includes at least one exterior facing imaging sensor or camera, such as a rearward facing imaging sensor or camera 14a (and the system may optionally include multiple exterior facing imaging sensors or cameras, such as a forwardly facing camera 14b at the front (or at the windshield) of the vehicle, and a sidewardly/rearwardly facing camera 14c, 14b at respective sides of the vehicle), which captures images exterior of the vehicle, with the camera having a lens for focusing images at or onto an imaging array or imaging plane or imager of the camera (FIG. 1). The vision system 12 includes a control or processor 18 that is operable to process image data captured by the cameras and may provide displayed images at a display device 16 for viewing by the driver of the vehicle (although shown in FIG. 1 as being part of or incorporated in or at an interior rearview mirror assembly 20 of the vehicle, the control and/or the display device may be disposed elsewhere at or in the vehicle).

The present invention provides algorithms that are used in vision systems and/or automotive cameras to identify and detect the degree that a lens on a camera is polluted by water droplets, mud or salt, so as to determine when the pollution is to a degree that the camera's performance may be substantially or severely reduced, and in automotive camera applications, when the driver's ability to use or view the camera's video is impaired or when the machine vision processor's performance is substantially or significantly impaired. It is desired that, in any of the described scenarios, the algorithms will determine the degree of pollution and give out warning signals, messages or directly control certain mechanisms to clean the lens of the camera. The present invention provides two pollution detection algorithms, where the first algorithm (which uses or requires a reduced amount of processing power) may be implemented directly in a camera and the second algorithm (which uses or requires more processing power) may be implemented in a control or electronic control unit (ECU) of the vehicle or a control of the vision system that may be separate and remote from the camera and/or camera circuitry.

Due to the minimum processing power and data bandwidth of an automotive rear view camera, it is not readily feasible to use image processing software on the microprocessor to identify the pollution, because such processing usually demands a high amount of processing power. The present invention thus provides a method for detecting pollution by reading a limited number of imager register values. The algorithm detects pollution by checking the contrast of auto exposure (AE) control zones when an AE function or feature is enabled and the camera's host vehicle is traveling in a forward or rearward direction or driving condition. Normally, in a typical camera imager (such as a two dimensional array of photosensing elements or pixels) used in automotive camera applications, the sensing area of the imager is divided into multiple zones (such as, for example, 5×5 zones or other sized zones) that allows each zone's pixels to be averaged in brightness and color values. The camera's or imager's auto exposure and auto white balance can be controlled by reading the zone brightness and color values of all zones. This first algorithm is based on the arithmetic calculations of the brightness values of all zones.

Tests on different roads at different times show that the contrast of AE zones has a large range (0-1) for a clean lens with little or no pollution and a small range (0-0.3) for a moderately polluted lens. To reliably detect the pollution on the lens, multiple AE zone contrasts (such as 10 used for the illustrated embodiment) are checked. Those AE zone contrasts includes the contrasts of the following AE zone pairs, 1-11, 2-12, 3-13, 4-14, 5-15, 6-16, 7-17, 8-18, 9-19, 10-20. The AE zone labels are shown in FIG. 2. As an example, in an Aptina CMOS imager MT9V128 (which is a CMOS imager with VGA resolution), the registers for corresponding AE zone brightness are listed in FIG. 3.

The basic concept of the first algorithm is as follows. In a typical automotive rear view camera, the scene imaged by the imager typically has the sky (above the horizon) imaged in the first or upper rows and the vehicle bumper in the last or lower row or rows, counting from top to bottom of the captured image. The middle rows of zones mostly image or show the road, ground, buildings, parked or passing vehicles and other objects. When the camera's host vehicle drives forward (or rearward) on the road, the zones in the middle rows will experience more changes of averaged brightness values of the zones than the ones in the top and bottom rows. By calculating the difference or contrast of the brightness values between the middle zones and zones in the top or bottom rows, either in the same column or the different column, the system can determine if a normal view is blocked or partially blocked, or polluted, by the substances (such as dirt, debris, moisture or the like) on the lens. In the case of a lens that is partially blocked, the contrast will be lower than the contrast of the same or similar zones with a clean lens. This is because when a part of camera lens is blocked by some substances (such as, for example, water droplets, salt, mud and/or the like), some light rays are blocked and cannot reach the imager as they normally do. As a result, some areas of the imager appear darker or have lower brightness values, and the contrast of the scene in these areas become lower.

Furthermore, when the vehicle moves along the road, the moving scene imaged by the imager generates less pixel value fluctuation or variation when the lens is polluted. The amount of reduced pixel value fluctuation grows with the amount of pollution on lens. In principle, one can compute the above values at every pixel of the imager, but doing so requires a significant amount of processing power and data transfer bandwidth. Instead, the system or process of the present invention uses the imager's existing average pixel brightness values of AE zones to compute the pollution level at the lens. This requires a reduced or minimum amount of computing power and data traffic. A microprocessor with limited processing power and with an I2C or SPI communication channel with the imager, which is typical for a rear view camera of a vehicle, is adequate for running the algorithm. The algorithm can also be built into the imager's system-on-chip (SOC) part to perform the above algorithm without using an external microprocessor.

Furthermore, the same algorithm can also be implemented in a separate processor that can calculate pollution level based only on the video input from a separate camera. In such a configuration or implementation, the computation can be based on pixel brightness or zone brightness average.

A flow chart of the pollution detection algorithm or process 110 is shown in FIG. 4. The process 110 starts at 102, and initializes a contrast maximum or max value and a contrast minimum or min value at 104. The process reads the registers for AE zone brightness for one frame at 106 (such as by reading AE zones 1-20), and calculates the current contrasts of interested AE zones at 108. If the system determines at 110 that the calculated contrast is greater than the contrast max value, then the contrast max value is set to the current contrast value at 112 and then the process continues to 114. However, if the system determines at 110 that the calculated contrast is not greater than the contrast max, then the process continues to 114. If the system determines at 114 that the calculated contrast is less than the contrast min value, then the contrast min value is set to the current contrast value at 116 and then the process continues to 118. However, if the system determines at 114 that the calculated contrast is not less than the contrast min value, then the process continues to 118. If the system has not completed the N iterations at 118, then the system returns to 106 and continues. If the system has completed the N iterations at 118, then the contrast range is set to be the difference between the contrast max and contrast min values at 120. If the system determines at 122 that the contrast range is less than a contrast threshold, then the system determines that there is pollution present at the lens (such as a threshold degree of pollution), and the system may generate an alert or report to report the pollution at 124 (such as providing a visual or audible report or alert to the driver of the vehicle). If the system determines at 122 that the contrast range is not less than a contrast threshold, then the system determines that there is no pollution (or there is less than a threshold amount of pollution) present at the lens and returns to 104 and repeats the process. Optionally, the system, responsive to a determination of pollution at the lens, may generate an alert or report and/or adapt the processing of image data to at least partially accommodate for the presence of the determined contaminants at the camera lens and/or clean the lens (such as via a fluid spray or wiping system or the like).

The second algorithm of the present invention preferably is implemented to run in a vehicle controller or control unit or ECU. Each pixel in the image is modeled as several Gaussians distributions. The system requires an initial training period (such as, for example, about 30 frames, or approximately 1 second of video) along with the scene changing (movement of the vehicle) in order to operate. If the vehicle remains stationary and the algorithm continued to run, all pixels would be flagged as not changing.

At each frame, the algorithm computes whether the pixel value remained static (the pixel value fit one of the Gaussian distributions) or the pixel value changed (the pixel value did not fit one of the Gaussian distributions). The Gaussian mixture model was chosen because it is robust to various lighting conditions, which leads to fewer numbers of false positives. When the number of pixels that have been classified as “not changing” exceeds a threshold (such as, for example, about 30 percent of the image or any suitable or selected percentage of the image), a blockage condition is identified. FIG. 5 depicts an example scene with this algorithm running, where the solid pixels or pixel areas 30 are representative of pixels that have not had any change.

FIG. 6 shows the flow chart of the second algorithm or ECU-based algorithm. The second algorithm or process 130 starts at 132 and, if the system determines at 134 that the vehicle is moving faster than a threshold level, then the system determines, at 136, whether or not the algorithm has been trained. If the system determines that the vehicle is not moving, then the process does not continue. If the vehicle is moving, but the algorithm has not been trained, then the system initializes the Gaussian distributions with the first 30 frames (or other suitable number of frames) of video images at 138 and then continues to 140, where the algorithm loops over each pixel in the new image. At 142, the system determines if the pixel fits one of the Gaussian distributions, and if so, it classifies the pixel as not changed or blocked at 144, and if not, the system classifies the pixel as changed at 146. The process then continues at 148, where the system determines whether or not the ratio of pixels classified as blocked is greater than a threshold level. If the ratio is greater than the threshold level, the system reports a blockage condition at 160. If the ratio is not greater than the threshold level, the system returns to 134 and continues.

Therefore, the present invention provides a vision system for a vehicle that includes a processor or head unit and a camera or cameras mounted at the vehicle. The system or process is operable to determine if there is pollution or dirt or contaminants present at a lens or cover of an exterior camera of a vehicle vision system (or an interiorly disposed camera that views through a cover or lens that may be exposed at the exterior of the vehicle). The system or process or algorithm may be incorporated in the circuitry of the camera or may be incorporated in a vehicle-based control or control of the vehicle or vision system. Optionally, a system or algorithm of the present invention (that may be operated or processed by the circuitry of the imager or camera) may be operable to read a limited number of imager register values, and may detect pollution by checking the contrast of auto exposure (AE) control zones when an AE function or feature is enabled and the camera's host vehicle is traveling in a forward (or rearward) direction or driving condition. When the range of contrast levels of the pixels are less than a threshold level, such that the contrast levels are not changing a threshold amount as the vehicle is moved, then the system or process or algorithm may determine that there is pollution or contaminants at the lens or cover of the imager.

Optionally, a system or algorithm of the present invention (that may be incorporated in or operated by a control of the vehicle or of the vehicle vision system and separate from the circuitry of the imager or camera) may be operable to process or monitor each pixel (or a substantial number of pixels) of an imager and if the pixel(s) fits a Gaussian distribution (that is based on a number of frames of the video images), the process or algorithm may classify the pixel as not changed or blocked, and then the system determines whether or not the ratio of pixels classified as blocked is greater than a threshold level, and if so, the system may determine a blockage condition.

Based on a result or output of either algorithm, the system may generate an alert to the driver of a blockage condition, or may clean the cover or lens (such as by utilizing aspects of the vision systems and cameras described in U.S. Pat. No. 7,965,336, which is hereby incorporated herein by reference in its entirety). Optionally, the system may, responsive to detection of or a determination of the presence of dirt or contaminants at the lens, adjust the processing of image data captured by that camera to accommodate or account for the determined dirt or contaminants that are present at the lens. Optionally, the system may utilize aspects of the dirt detection and camera protection systems described in U.S. provisional applications, Ser. No. 61/713,772, filed Oct. 15, 2012; Ser. No. 61/766,883, filed Feb. 20, 2013; and/or Ser. No. 61/804,786, filed Mar. 25, 2013, which are hereby incorporated herein by reference in their entireties.

The system includes an image processor operable to process image data captured by the camera or cameras, such as for detecting objects or other vehicles or pedestrians or the like in the field of view of one or more of the cameras. For example, the image processor may comprise an EyeQ2 or EyeQ3 image processing chip available from Mobileye Vision Technologies Ltd. of Jerusalem, Israel, and may include object detection software (such as the types described in U.S. Pat. Nos. 7,855,755; 7,720,580 and/or 7,038,577, which are hereby incorporated herein by reference in their entireties), and may analyze image data to detect vehicles and/or other objects. Responsive to such image processing, and when an object or other vehicle is detected, the system may generate an alert to the driver of the vehicle and/or may generate an overlay at the displayed image to highlight or enhance display of the detected object or vehicle, in order to enhance the driver's awareness of the detected object or vehicle or hazardous condition during a driving maneuver of the equipped vehicle.

The vehicle may include any type of sensor or sensors, such as imaging sensors or radar sensors or lidar sensors or ladar sensors or ultrasonic sensors or the like. The imaging sensor or camera may capture image data for image processing and may comprise any suitable camera or sensing device, such as, for example, an array of a plurality of photosensor elements arranged in at least 640 columns and 480 rows (at least a 640×480 imaging array and optionally a mega-pixel array that provides high definition imaging), with a respective lens focusing images onto respective portions of the array. The photosensor array may comprise a plurality of photosensor elements arranged in a photosensor array having rows and columns. The logic and control circuit of the imaging sensor may function in any known manner, and the image processing and algorithmic processing may comprise any suitable means for processing the images and/or image data. For example, the vision system and/or processing and/or camera and/or circuitry may utilize aspects described in U.S. Pat. Nos. 7,005,974; 5,760,962; 5,877,897; 5,796,094; 5,949,331; 6,222,447; 6,302,545; 6,396,397; 6,498,620; 6,523,964; 6,611,202; 6,201,642; 6,690,268; 6,717,610; 6,757,109; 6,802,617; 6,806,452; 6,822,563; 6,891,563; 6,946,978; 7,859,565; 5,550,677; 5,670,935; 6,636,258; 7,145,519; 7,161,616; 7,230,640; 7,248,283; 7,295,229; 7,301,466; 7,592,928; 7,881,496; 7,720,580; 7,038,577; 6,882,287; 5,929,786 and/or 5,786,772, and/or PCT Application No. PCT/US2010/047256, filed Aug. 31, 2010 and published Mar. 10, 2011 as International Publication No. WO 2011/028686 and/or International Publication No. WO 2010/099416, published Sep. 2, 2010, and/or PCT Application No. PCT/US10/25545, filed Feb. 26, 2010 and published Sep. 2, 2010 as International Publication No. WO 2010/099416, and/or PCT Application No. PCT/US2012/048800, filed Jul. 30, 2012 and published Feb. 7, 2013 as International Publication No. WO 2013/019707, and/or PCT Application No. PCT/US2012/048110, filed Jul. 25, 2012 and published Jan. 31, 2013 as International Publication No. WO 2013/016409, and/or PCT Application No. PCT/CA2012/000378, filed Apr. 25, 2012 and published Nov. 1, 2012 as International Publication No. WO 2012/145822, and/or PCT Application No. PCT/US2012/056014, filed Sep. 19, 2012 and published Mar. 28, 2013 as International Publication No. WO 2013/043661, and/or PCT Application No. PCT/US12/57007, filed Sep. 25, 2012 and published Apr. 4, 2013 as International Publication No. WO 2013/048994, and/or PCT Application No. PCT/US2012/061548, filed Oct. 24, 2012 and published May 2, 2013 as International Publication No. WO 2013/063014, and/or PCT Application No. PCT/US2012/062906, filed Nov. 1, 2012 and published May 10, 2013 as International Publication No. WO 2013/067083, and/or PCT Application No. PCT/US2012/063520, filed Nov. 5, 2012 and published May 16, 2013 as International Publication No. WO 2013/070539, and/or PCT Application No. PCT/US2012/064980, filed Nov. 14, 2012 and published May 23, 2013 as International Publication No. WO 2013/074604, and/or PCT Application No. PCT/US2012/066570, filed Nov. 27, 2012 and published Jun. 6, 2013 as International Publication No. WO 2013/081984, and/or PCT Application No. PCT/US2012/066571, filed Nov. 27, 2012 and published Jun. 6, 2013 as International Publication No. WO 2013/081985, and/or PCT Application No. PCT/US2012/068331, filed Dec. 7, 2012 and published Jun. 13, 2013 as International Publication No. WO 2013/086249, and/or PCT Application No. PCT/US2013/022119, filed Jan. 18, 2013 and published Jul. 25, 2013 as International Publication No. WO 2013/109869, and/or PCT Application No. PCT/US2013/027342, filed Feb. 22, 2013 and published Aug. 29, 2013 as International Publication No. WO 2013/126715, and/or U.S. patent application Ser. No. 13/848,796, filed Mar. 22, 2013 and published Oct. 24, 2013 as U.S. Publication No. US-2013-0278769; Ser. No. 13/847,815, filed Mar. 20, 2013 and published Oct. 31, 2013 as U.S. Publication No. US-2013-0286193; Ser. No. 13/779,881, filed Feb. 28, 2013 and published Sep. 5, 2013 as U.S. Publication No. US-2013-0231825; Ser. No. 13/785,099, filed Mar. 5, 2013 and published Sep. 19, 2013 as U.S. Publication No. US-2013-0242099; Ser. No. 13/774,317, filed Feb. 22, 2013, now U.S. Pat. No. 9,269,263; Ser. No. 13/774,315, filed Feb. 22, 2013 and published Aug. 22, 2013 as U.S. Publication No. US-2013-0215271; Ser. No. 13/681,963, filed Nov. 20, 2012, now U.S. Pat. No. 9,264,673; Ser. No. 13/660,306, filed Oct. 25, 2012, now U.S. Pat. No. 9,146,898; Ser. No. 13/653,577, filed Oct. 17, 2012, now U.S. Pat. No. 9,174,574; and/or Ser. No. 13/534,657, filed Jun. 27, 2012 and published Jan. 3, 2013 as U.S. Publication No. US-2013-0002873, and/or U.S. provisional applications, Ser. No. 61/733,598, filed Dec. 5, 2012; Ser. No. 61/733,093, filed Dec. 4, 2012; Ser. No. 61/710,924, filed Oct. 8, 2012; Ser. No. 61/696,416, filed Sep. 4, 2012; Ser. No. 61/682,995, filed Aug. 14, 2012; Ser. No. 61/682,486, filed Aug. 13, 2012; Ser. No. 61/680,883, filed Aug. 8, 2012; Ser. No. 61/678,375, filed Aug. 1, 2012; Ser. No. 61/676,405, filed Jul. 27, 2012; Ser. No. 61/666,146, filed Jun. 29, 2012; Ser. No. 61/653,665, filed May 31, 2012; Ser. No. 61/653,664, filed May 31, 2012; Ser. No. 61/648,744, filed May 18, 2012; and/or Ser. No. 61/624,507, filed Apr. 16, 2012, which are all hereby incorporated herein by reference in their entireties. The system may communicate with other communication systems via any suitable means, such as by utilizing aspects of the systems described in PCT Application No. PCT/US10/038477, filed Jun. 14, 2010, and/or U.S. patent application Ser. No. 13/202,005, filed Aug. 17, 2011, now U.S. Pat. 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The imaging device and control and image processor and any associated illumination source, if applicable, may comprise any suitable components, and may utilize aspects of the cameras and vision systems described in U.S. Pat. Nos. 5,550,677; 5,877,897; 6,498,620; 5,670,935; 5,796,094; 6,396,397; 6,806,452; 6,690,268; 7,005,974; 7,123,168; 7,004,606; 6,946,978; 7,038,577; 6,353,392; 6,320,176; 6,313,454 and 6,824,281, and/or International Publication No. WO 2010/099416, published Sep. 2, 2010, and/or PCT Application No. PCT/US10/47256, filed Aug. 31, 2010 and published Mar. 10, 2011 as International Publication No. WO 2011/028686, and/or U.S. patent application Ser. No. 12/508,840, filed Jul. 24, 2009, and published Jan. 28, 2010 as U.S. Pat. Publication No. US 2010-0020170, and/or PCT Application No. PCT/US2012/048110, filed Jul. 25, 2012 and published Jan. 31, 2013 as International Publication No. WO 2013/016409, and/or U.S. patent application Ser. No. 13/534,657, filed Jun. 27, 2012 and published Jan. 3, 2013 as U.S. Publication No. US-2013-0002873, which are all hereby incorporated herein by reference in their entireties. The camera or cameras may comprise any suitable cameras or imaging sensors or camera modules, and may utilize aspects of the cameras or sensors described in U.S. patent application Ser. No. 12/091,359, filed Apr. 24, 2008 and published Oct. 1, 2009 as U.S. Publication No. US-2009-0244361, and/or Ser. No. 13/260,400, filed Sep. 26, 2011, now U.S. Pat. No. 8,542,451, and/or U.S. Pat. No. 7,965,336 and/or 7,480,149, which are hereby incorporated herein by reference in their entireties. The imaging array sensor may comprise any suitable sensor, and may utilize various imaging sensors or imaging array sensors or cameras or the like, such as a CMOS imaging array sensor, a CCD sensor or other sensors or the like, such as the types described in U.S. Pat. Nos. 5,550,677; 5,670,935; 5,760,962; 5,715,093; 5,877,897; 6,922,292; 6,757,109; 6,717,610; 6,590,719; 6,201,642; 6,498,620; 5,796,094; 6,097,023; 6,320,176; 6,559,435; 6,831,261; 6,806,452; 6,396,397; 6,822,563; 6,946,978; 7,339,149; 7,038,577; 7,004,606 and/or 7,720,580, and/or U.S. patent application Ser. No. 10/534,632, filed May 11, 2005, now U.S. Pat. No. 7,965,336; and/or PCT Application No. PCT/US2008/076022, filed Sep. 11, 2008 and published Mar. 19, 2009 as International Publication No. WO/2009/036176, and/or PCT Application No. PCT/US2008/078700, filed Oct. 3, 2008 and published Apr. 9, 2009 as International Publication No. WO/2009/046268, which are all hereby incorporated herein by reference in their entireties.

The camera module and circuit chip or board and imaging sensor may be implemented and operated in connection with various vehicular vision-based systems, and/or may be operable utilizing the principles of such other vehicular systems, such as a vehicle headlamp control system, such as the type disclosed in U.S. Pat. Nos. 5,796,094; 6,097,023; 6,320,176; 6,559,435; 6,831,261; 7,004,606; 7,339,149 and/or 7,526,103, which are all hereby incorporated herein by reference in their entireties, a rain sensor, such as the types disclosed in commonly assigned U.S. Pat. Nos. 6,353,392; 6,313,454; 6,320,176 and/or 7,480,149, which are hereby incorporated herein by reference in their entireties, a vehicle vision system, such as a forwardly, sidewardly or rearwardly directed vehicle vision system utilizing principles disclosed in U.S. Pat. Nos. 5,550,677; 5,670,935; 5,760,962; 5,877,897; 5,949,331; 6,222,447; 6,302,545; 6,396,397; 6,498,620; 6,523,964; 6,611,202; 6,201,642; 6,690,268; 6,717,610; 6,757,109; 6,802,617; 6,806,452; 6,822,563; 6,891,563; 6,946,978 and/or 7,859,565, which are all hereby incorporated herein by reference in their entireties, a trailer hitching aid or tow check system, such as the type disclosed in U.S. Pat. No. 7,005,974, which is hereby incorporated herein by reference in its entirety, a reverse or sideward imaging system, such as for a lane change assistance system or lane departure warning system or for a blind spot or object detection system, such as imaging or detection systems of the types disclosed in U.S. Pat. Nos. 7,720,580; 7,038,577; 5,929,786 and/or 5,786,772, and/or U.S. patent application Ser. No. 11/239,980, filed Sep. 30, 2005, now U.S. Pat. No. 7,881,496, and/or U.S. provisional applications, Ser. No. 60/628,709, filed Nov. 17, 2004; Ser. No. 60/614,644, filed Sep. 30, 2004; Ser. No. 60/618,686, filed Oct. 14, 2004; Ser. No. 60/638,687, filed Dec. 23, 2004, which are hereby incorporated herein by reference in their entireties, a video device for internal cabin surveillance and/or video telephone function, such as disclosed in U.S. Pat. Nos. 5,760,962; 5,877,897; 6,690,268 and/or 7,370,983, and/or U.S. patent application Ser. No. 10/538,724, filed Jun. 13, 2005 and published Mar. 9, 2006 as U.S. Publication No. US-2006-0050018, which are hereby incorporated herein by reference in their entireties, a traffic sign recognition system, a system for determining a distance to a leading or trailing vehicle or object, such as a system utilizing the principles disclosed in U.S. Pat. No. 6,396,397 and/or 7,123,168, which are hereby incorporated herein by reference in their entireties, and/or the like.

Optionally, the circuit board or chip may include circuitry for the imaging array sensor and or other electronic accessories or features, such as by utilizing compass-on-a-chip or EC driver-on-a-chip technology and aspects such as described in U.S. Pat. No. 7,255,451 and/or U.S. Pat. No. 7,480,149; and/or U.S. patent application Ser. No. 11/226,628, filed Sep. 14, 2005 and published Mar. 23, 2006 as U.S. Publication No. US-2006-0061008, and/or Ser. No. 12/578,732, filed Oct. 14, 2009 and published Apr. 22, 2012 as U.S. Publication No. US-2010-0097469, which are hereby incorporated herein by reference in their entireties.

Optionally, the vision system may include a display for displaying images captured by one or more of the imaging sensors for viewing by the driver of the vehicle while the driver is normally operating the vehicle. Optionally, for example, the vision system may include a video display device disposed at or in the interior rearview mirror assembly of the vehicle, such as by utilizing aspects of the video mirror display systems described in U.S. Pat. No. 6,690,268 and/or U.S. patent application Ser. No. 13/333,337, filed Dec. 21, 2011, now U.S. Pat. No. 9,264,672, which are hereby incorporated herein by reference in their entireties. The video mirror display may comprise any suitable devices and systems and optionally may utilize aspects of the compass display systems described in U.S. Pat. Nos. 7,370,983; 7,329,013; 7,308,341; 7,289,037; 7,249,860; 7,004,593; 4,546,551; 5,699,044; 4,953,305; 5,576,687; 5,632,092; 5,677,851; 5,708,410; 5,737,226; 5,802,727; 5,878,370; 6,087,953; 6,173,508; 6,222,460; 6,513,252 and/or 6,642,851, and/or European patent application, published Oct. 11, 2000 under Publication No. EP 0 1043566, and/or U.S. patent application Ser. No. 11/226,628, filed Sep. 14, 2005 and published Mar. 23, 2006 as U.S. Publication No. US-2006-0061008, which are all hereby incorporated herein by reference in their entireties. Optionally, the video mirror display screen or device may be operable to display images captured by a rearward viewing camera of the vehicle during a reversing maneuver of the vehicle (such as responsive to the vehicle gear actuator being placed in a reverse gear position or the like) to assist the driver in backing up the vehicle, and optionally may be operable to display the compass heading or directional heading character or icon when the vehicle is not undertaking a reversing maneuver, such as when the vehicle is being driven in a forward direction along a road (such as by utilizing aspects of the display system described in PCT Application No. PCT/US2011/056295, filed Oct. 14, 2011 and published Apr. 19, 2012 as International Publication No. WO 2012/051500, which is hereby incorporated herein by reference in its entirety).

Optionally, the vision system (utilizing the forward facing camera and a rearward facing camera and other cameras disposed at the vehicle with exterior fields of view) may be part of or may provide a display of a top-down view or birds-eye view system of the vehicle or a surround view at the vehicle, such as by utilizing aspects of the vision systems described in PCT Application No. PCT/US10/25545, filed Feb. 26, 2010 and published on Sep. 2, 2010 as International Publication No. WO 2010/099416, and/or PCT Application No. PCT/US10/47256, filed Aug. 31, 2010 and published Mar. 10, 2011 as International Publication No. WO 2011/028686, and/or PCT Application No. PCT/US2011/062834, filed Dec. 1, 2011 and published Jun. 7, 2012 as International Publication No. WO2012/075250, and/or PCT Application No. PCT/US2012/048993, filed Jul. 31, 2012 and published Feb. 7, 2013 as International Publication No. WO 2013/019795, and/or PCT Application No. PCT/US11/62755, filed Dec. 1, 2011 and published Jun. 7, 2012 as International Publication No. WO 2012-075250, and/or PCT Application No. PCT/CA2012/000378, filed Apr. 25, 2012 and published Nov. 1, 2012 as International Publication No. WO 2012/145822, and/or PCT Application No. PCT/US2012/066571, filed Nov. 27, 2012 and published Jun. 6, 2013 as International Publication No. WO 2013/081985, and/or PCT Application No. PCT/US2012/068331, filed Dec. 7, 2012 and published Jun. 13, 2013 as International Publication No. WO 2013/086249, and/or PCT Application No. PCT/US2013/022119, filed Jan. 18, 2013 and published Jul. 25, 2013 as International Publication No. WO 2013/109869, and/or U.S. patent application Ser. No. 13/333,337, filed Dec. 21, 2011, now U.S. Pat. No. 9,264,672, which are hereby incorporated herein by reference in their entireties.

Optionally, a video mirror display may be disposed rearward of and behind the reflective element assembly and may comprise a display such as the types disclosed in U.S. Pat. Nos. 5,530,240; 6,329,925; 7,855,755; 7,626,749; 7,581,859; 7,446,650; 7,370,983; 7,338,177; 7,274,501; 7,255,451; 7,195,381; 7,184,190; 5,668,663; 5,724,187 and/or 6,690,268, and/or in U.S. patent application Ser. No. 12/091,525, filed Apr. 25, 2008, now U.S. Pat. No. 7,855,755; Ser. No. 11/226,628, filed Sep. 14, 2005 and published Mar. 23, 2006 as U.S. Publication No. US-2006-0061008; and/or Ser. No. 10/538,724, filed Jun. 13, 2005 and published Mar. 9, 2006 as U.S. Publication No. US-2006-0050018, which are all hereby incorporated herein by reference in their entireties. The display is viewable through the reflective element when the display is activated to display information. The display element may be any type of display element, such as a vacuum fluorescent (VF) display element, a light emitting diode (LED) display element, such as an organic light emitting diode (OLED) or an inorganic light emitting diode, an electroluminescent (EL) display element, a liquid crystal display (LCD) element, a video screen display element or backlit thin film transistor (TFT) display element or the like, and may be operable to display various information (as discrete characters, icons or the like, or in a multi-pixel manner) to the driver of the vehicle, such as passenger side inflatable restraint (PSIR) information, tire pressure status, and/or the like. The mirror assembly and/or display may utilize aspects described in U.S. Pat. Nos. 7,184,190; 7,255,451; 7,446,924 and/or 7,338,177, which are all hereby incorporated herein by reference in their entireties. The thicknesses and materials of the coatings on the substrates of the reflective element may be selected to provide a desired color or tint to the mirror reflective element, such as a blue colored reflector, such as is known in the art and such as described in U.S. Pat. Nos. 5,910,854; 6,420,036 and/or 7,274,501, which are hereby incorporated herein by reference in their entireties.

Optionally, the display or displays and any associated user inputs may be associated with various accessories or systems, such as, for example, a tire pressure monitoring system or a passenger air bag status or a garage door opening system or a telematics system or any other accessory or system of the mirror assembly or of the vehicle or of an accessory module or console of the vehicle, such as an accessory module or console of the types described in U.S. Pat. Nos. 7,289,037; 6,877,888; 6,824,281; 6,690,268; 6,672,744; 6,386,742 and 6,124,886, and/or U.S. patent application Ser. No. 10/538,724, filed Jun. 13, 2005 and published Mar. 9, 2006 as U.S. Publication No. US-2006-0050018, which are hereby incorporated herein by reference in their entireties.

Changes and modifications to the specifically described embodiments may be carried out without departing from the principles of the present invention, which is intended to be limited only by the scope of the appended claims as interpreted according to the principles of patent law.

Claims

1. A vision system for a vehicle, said vision system comprising: a camera disposed at a vehicle and having a field of view exterior of the vehicle, said camera operable to capture frames of image data;wherein said camera comprises a lens and an imager comprising an array of photosensing elements having multiple columns of photosensing elements and multiple rows of photosensing elements;a processor operable to process image data captured by said camera;wherein, with the vehicle moving, and with said camera capturing image data, said processor models outputs of photosensing elements as Gaussian distributions;wherein, with the vehicle moving, and with said camera capturing frames of image data, said processor determines an output of respective ones of said modeled photosensing elements over multiple frames of captured image data;wherein, with the vehicle moving, and with said camera capturing frames of image data, said processor determines whether the output of a modeled photosensing element fits the respective Gaussian distribution for that photosensing element;wherein, responsive to determination that the output of the modeled photosensing element fits within the respective Gaussian distribution for that photosensing element, said vision system classifies that photosensing element as a blocked element;wherein, responsive to determination that the output of the modeled photosensing element does not fit within the respective Gaussian distribution for that photosensing element, said vision system classifies that photosensing element as a not blocked element; andwherein, responsive to determination over multiple frames of captured image data that the ratio of the number of photosensing elements classified as a blocked element to the number of photosensing elements classified as a not blocked element is greater than a threshold ratio, a blockage condition is determined.

2. The vision system of claim 1, wherein the threshold ratio comprises at least a thirty percent ratio of blocked elements to not blocked elements.

3. The vision system of claim 1, wherein said processor models outputs of photosensing elements as respective Gaussian distributions during an initialization period.

4. The vision system of claim 1, wherein, when the vehicle is not moving, said vision system does not determine, for each frame of captured image data, whether outputs of modeled photosensing elements fit within respective Gaussian distributions for those photosensing elements.

5. The vision system of claim 1, wherein, responsive to a blockage condition being determined, said system at least one of (i) generates an alert, (ii) adapts processing of captured image data to at least partially accommodate for the blockage condition and (iii) cleans said lens.

6. The vision system of claim 1, wherein said processor is incorporated in circuitry of said camera.

7. The vision system of claim 1, wherein said processor is incorporated in circuitry of an electronic control unit of the vehicle.

8. The vision system of claim 1, wherein the vehicle moving comprises the vehicle being driven forward on a road.

9. The vision system of claim 1, wherein said camera comprises a CMOS camera.

10. The vision system of claim 9, wherein said imager comprises at least 640 columns of photosensing elements and at least 480 rows of photosensing elements.

11. The vision system of claim 1, wherein said camera is part of a multi-camera birds-eye surround view system of the equipped vehicle.

12. A vision system for a vehicle, said vision system comprising: a camera disposed at a vehicle and having a field of view exterior of the vehicle, said camera operable to capture frames of image data;wherein said camera comprises a lens and an imager comprising an array of photosensing elements having multiple columns of photosensing elements and multiple rows of photosensing elements;a processor operable to process image data captured by said camera;wherein, with the vehicle moving, and with said camera capturing image data, said processor models outputs of photosensing elements as Gaussian distributions;wherein said processor models outputs of photosensing elements as respective Gaussian distributions during an initialization period;wherein, with the vehicle moving after the initialization period, and with said camera capturing frames of image data, said processor determines an output of respective ones of said modeled photosensing elements over multiple frames of captured image data;wherein, with the vehicle moving, and with said camera capturing frames of image data, said processor determines whether the output of a modeled photosensing element fits within the respective Gaussian distribution for that photosensing element;wherein, responsive to determination that the output of the modeled photosensing element fits within the respective Gaussian distribution for that photosensing element, said vision system classifies that photosensing element as a blocked element;wherein, responsive to determination that the output of the modeled photosensing element does not fit within the respective Gaussian distribution for that photosensing element, said vision system classifies that photosensing element as a not blocked element;wherein, responsive to determination over multiple frames of captured image data that the ratio of the number of photosensing elements classified as a blocked element to the number of photosensing elements classified as a not blocked element is greater than a threshold ratio, a blockage condition is determined; andwherein, when the vehicle is not moving, said vision system does not determine, for each frame of captured image data, whether outputs of modeled photosensing elements fit within respective Gaussian distributions for those photosensing elements.

13. The vision system of claim 12, wherein the threshold ratio comprises at least a thirty percent ratio of blocked elements to not blocked elements.

14. The vision system of claim 12, wherein, responsive to a blockage condition being determined, said system at least one of (i) generates an alert, (ii) adapts processing of captured image data to at least partially accommodate for the blockage condition and (iii) cleans said lens.

15. The vision system of claim 12, wherein said processor is incorporated in circuitry of said camera.

16. The vision system of claim 12, wherein said processor is incorporated in circuitry of an electronic control unit of the vehicle.

17. The vision system of claim 12, wherein the vehicle moving comprises the vehicle being driven forward on a road.

18. A vision system for a vehicle, said vision system comprising: a camera disposed at a vehicle and having a field of view exterior of the vehicle, said camera operable to capture frames of image data;wherein said camera comprises a lens and an imager comprising an array of photosensing elements having multiple columns of photosensing elements and multiple rows of photosensing elements;a processor operable to process image data captured by said camera;wherein, with the vehicle driven forward along a road, and with said camera capturing image data, said processor models outputs of photosensing elements as Gaussian distributions;wherein said processor models outputs of photosensing elements as respective Gaussian distributions during an initialization period;wherein, with the vehicle driven forward along the road after the initialization period, and with said camera capturing frames of image data, said processor determines an output of respective ones of said modeled photosensing elements for each frame of captured image data;wherein, with the vehicle driven forward along the road, and with said camera capturing frames of image data, said processor determines whether the output of a modeled photosensing element fits within the respective Gaussian distribution for that photosensing element;wherein, responsive to determination that the output of the modeled photosensing element fits within the respective Gaussian distribution for that photosensing element, said vision system classifies that photosensing element as a blocked element;wherein, responsive to determination that the output of the modeled photosensing element does not fit within the respective Gaussian distribution for that photosensing element, said vision system classifies that photosensing element as a not blocked element;wherein, responsive to determination over multiple frames of captured image data that the ratio of the number of photosensing elements classified as a blocked element to the number of photosensing elements classified as a not blocked element is greater than a threshold ratio, a blockage condition is determined; andwherein, responsive to a blockage condition being determined, said system at least one of (i) generates an alert, (ii) adapts processing of captured image data to at least partially accommodate for the blockage condition and (iii) cleans said lens.

19. The vision system of claim 18, wherein said processor is incorporated in circuitry of said camera.

20. The vision system of claim 18, wherein said processor is incorporated in circuitry of an electronic control unit of the vehicle.