Patent Application
20100188528
This application is based upon and claims the benefit of priority from the prior Japanese Patent Application No. 2009-017045, filed on Jan. 28, 2009, and the prior Japanese Patent Application No. 2009-017046, filed on Jan. 28, 2009; the entire contents of which are incorporated herein by reference.
1. Field of the Invention
The present invention relates to an image recording device, a manufacturing apparatus of an image recording device, and a manufacturing method of an image recording device.
2. Description of the Related Art
Conventionally, a camera module as an image recording device used for a digital camera and the like that converts an image of a captured subject to image data and electronically stores the image therein has been known. The image quality of images captured by such an image recording device degrades due to occurrence of density distortion, geometrical distortion, or blur, due mainly to optical aberrations. Generally, edge enhancement filtering is performed to reduce unnecessary information and to extract useful information from the degraded images. Further, there is an image restoration technique as a technique for acquiring highly accurate images. There are various types of the image restoration technique, and for example, a restoring process using a point spread function (PSF), which is an optical transfer function, is proposed in Japanese Patent Application Laid-Open No. 2007-183842.
However, there is a problem that, although it is possible to calculate the PSF with respect to a design value of a lens used for an image recording device, restoration of the optical distortion due to a lens manufacturing error and an error at the time of assembling the image recording device is difficult. In the present application, the difference for each image recording device generated due to a lens manufacturing error and an error at the time of assembling the image recording device is referred to as “individual difference”.
Conventionally, to improve the quality of image data acquired by an image recording device, high accuracy has been required at the time of manufacturing lenses and assembling image recording devices. Therefore, there is another problem that the cost of parts and assembly processes are increased. Further, the requirement of high accuracy at the time of manufacturing lenses and assembling image recording devices causes a decrease in yield, thereby incurring a further cost increase.
An image recording device according to an embodiment of the present invention comprises: An image recording device that records captured image data, the image recording device comprising: an image sensor that converts light from a subject to a signal charge to acquire the image data;a memory that holds measured PSF data indicating a PSF of at least one area of the image sensor virtually divided into a plurality of areas; and a restoring unit that restores the image data by using the measured PSF data, wherein the measured PSF data is acquired from captured data acquired by capturing an adjustment chart for virtually dividing the image sensor into a plurality of areas by the image recording device.
A manufacturing apparatus of an image recording device according to an embodiment of the present invention comprises: a manufacturing apparatus of an image recording device comprising: a capturing unit that causes an image recording device to capture an adjustment chart for virtually dividing an image sensor provided in the image recording device into a plurality of areas; and an input unit that inputs measured PSF data indicating a PSF of the areas acquired from captured data of the adjustment chart captured by the image recording device to a memory provided in the image recording device so that the measured PSF data is held therein.
A manufacturing method of an image recording device according to an embodiment of the present invention comprises: a manufacturing method of an image recording device comprising an imaging lens that takes light from a subject and an image sensor that converts light from the subject to a signal charge to acquire image data, the manufacturing method comprising: assembling the image recording device by adjusting a distance between the imaging lens and the image sensor; causing the image recording device to capture an adjustment chart for virtually dividing the image sensor into a plurality of areas; and holding including inputting measured PSF data indicating a PSF of the areas acquired from captured data of the adjustment chart captured by the image recording device to a memory provided in the image recording device, and holding the measured PSF data therein.
Exemplary embodiments of an image recording device, a manufacturing apparatus of an image recording device, and a manufacturing method of an image recording device according to the present invention will be explained below in detail with reference to the accompanying drawings. The present invention is not limited to the following embodiments.
A configuration of a camera module (image recording device) 1 is explained first.
A configuration of a manufacturing apparatus 20 of the camera module 1 is explained next.
The adjustment chart 24 is captured by the camera module 1 for acquiring the PSF data held in the PSF memory 6. When the camera module 1 captures the adjustment chart 24, the entire surface of the image sensor 4 is virtually divided into nine areas (areas Q1 to Q9) of 3×3 (rows by columns). The adjustment chart 24 is a point image chart including point images so that the PSF data can be acquired by captured data. A positional relation between the mounting portion 22 and the adjustment chart 24 is set to be a positional relation suitable for capturing the adjustment chart 24 by the camera module 1 mounted on the mounting portion 22.
The controller 26 controls the camera module 1 mounted on the mounting portion 22. Specifically, the controller 26 causes the camera module 1 mounted on the mounting portion 22 to capture the adjustment chart 24. That is, the controller 26 functions as a chart capturing unit to cause the camera module 1 to capture the adjustment chart.
A process of holding the PSF data in the PSF memory 6 included in the camera module 1 is explained next.
A process of correcting the image data captured by the camera module 1 is explained next. The camera module 1 first captures a subject (Step S11). Accordingly, a raw image can be acquired as image data of the subject. The image correcting unit 8 performs noise reduction with respect to the raw image (Step S12). The image correcting unit 8 then performs a restoring process using the measured PSF data p1 to p9 with respect to the raw image (Step S13).
A restoration effect depends on an image restoration algorithm, and for example, an image restoration method by the Richardson-Lucy method can be used. Accordingly, an image close to an actual image with less optical strain or blur can be acquired. Even if there is a manufacturing error of the imaging lens 2, an image close to an actual image can be acquired by the restoring process explained in the first embodiment, thereby enabling to suppress the manufacturing accuracy required for the imaging lens 2 and reduce the manufacturing cost. Further, even if there is an assembly error in the camera module 1, the assembly accuracy required for the camera module 1 can be relaxed and the manufacturing cost can be reduced, because an image close to the actual image can be acquired by the restoring process.
The adjustment chart 24 is a point image chart including point images; however, it is not limited thereto, and the adjustment chart 24 can be a chart in which the captured data in the respective areas Q1 to Q9 can be used as the PSF data or a chart in which the pieces of captured data are images having a strong correlation with the PSF data.
The adjustment chart 24 is divided into nine areas of 3×3; however, it can be divided into M×N areas of M rows by N columns, where M and N are integers. As M×N becomes larger, the accuracy of the restoring process can be improved.
The dividing direction is not limited to a matrix shape and it can be a curvilinear coordinate, for example. The number of divisions does not depend on the dividing direction, and can be arbitrary two points. The PSF data is not limited to image data. For example, a PSF image table can be held in a separate ROM, and the PSF memory 6 can hold difference data with respect to the PSF image data and a ratio coefficient. When the difference data and the ratio coefficient have a small capacity as compared with the image data, the capacity of the PSF memory 6 included in the camera module 1 can be made small.
The PSF data can be held in an external memory instead of the PSF memory 6 in the camera module 1. An algorithm different from that of the Richardson-Lucy method can be used as the algorithm of image restoration.
A second embodiment of the present invention is explained with reference to
In the second embodiment, the controller 26 estimates more pieces of PSF data based on the measured PSF data p1 to p9 acquired from the adjustment chart 24. The controller 26 functions as an estimating unit that estimates the PSF data.
The restoring process of the captured image is performed by using the 6561 PSF data (measured PSF data and estimated PSF data) held in the PSF memory 6 with respect to the raw image having subjected to noise reduction similarly to the first embodiment (Steps S31 to S34).
Generally, even in the same area T1, the PSF is different for each area. In the first embodiment, the measured PSF data p1 is adopted as the PSF data representing the area T1, and the measured PSF data p1 is applied to the entire area T1 to restore the image data. On the other hand, in the second embodiment, the controller 26 further subdivides the area T1, and estimates the PSF data for each subdivided area to acquire the estimated PSF data. Because the restoring process is performed by using the estimated PSF data, a more accurate restoring process can be realized.
In the second embodiment, the controller 26 separate from the camera module 1 has a function as an estimating unit that estimates the estimated PSF data, however, the estimating unit can be provided in the camera module 1.
The adjustment chart 24 is divided into nine areas of 3×3; however, it can be divided into M×N areas of M rows by N columns (M and N are integers). As M×N becomes larger, the accuracy of the restoring process can be improved.
Further, the dividing direction is not limited to a matrix shape, and can be a curvilinear coordinate, for example. The number of divisions does not depend on the dividing direction, and can be arbitrary two points. The PSF data is not limited to image data. For example, a PSF image table can be held in a separate ROM, and the PSF memory 6 can hold difference data with respect to the PSF image data and a ratio coefficient. When the difference data and the ratio coefficient have a small capacity as compared with the image data, the capacity of the PSF memory 6 included in the camera module 1 can be made small.
An estimation approximation method of the PSF data is not limited to the least square method, and other methods can be used. The PSF data can be held not in the PSF memory but in an external memory. An algorithm different from that of the Richardson-Lucy method can be used as the algorithm of image restoration. The controller 26 can calculate the aberration components in advance, and not the PSF data but the aberration components can be held in the PSF memory.
A third embodiment of the present invention is explained with reference to
In the third embodiment, the controller 26 acquires the basic aberration amount such as spherical aberrations, coma-aberrations, and astigmatism, which are third-order aberrations, and a wavefront aberration amount such as an out-of-focus amount by performing Fourier transform for nine pieces of PSF data acquired by the same process as in the second embodiment.
Generally, even in the same area T1, the PSF is different for each area. In the first embodiment, the measured PSF data p1 is adopted as the PSF data representing the area T1, and the measured PSF data p1 is applied to the entire area T1 to restore the image data. On the other hand, in the third embodiment, the controller 26 further subdivides the area T1, and estimates the PSF data for each subdivided area to acquire the estimated PSF data. Because the restoring process is performed by using the estimated PSF data, a more accurate restoring process can be realized.
Furthermore, in the third embodiment, because the measured PSF data p1 to p9 are Fourier-transformed to acquire the aberration components, respective aberration components Z3 to Z8 can be handled as complete independent components, and the PSF data can be estimated more accurately. Accordingly, a more accurate restoring process can be realized.
In the third embodiment, the controller 26 separate from the camera module 1 has a function as an estimating unit that estimates the PSF data; however, the estimating unit can be separately provided in the camera module 1.
The adjustment chart 24 is divided into nine areas of 3×3; however, it can be divided into M×N areas of M rows by N columns (M and N are integers). As M×N becomes larger, the accuracy of the restoring process can be improved.
The dividing direction is not limited to a matrix shape, and can be a curvilinear coordinate, for example. The number of divisions does not depend on the dividing direction, and can be arbitrary two points. The PSF data is not limited to image data. For example, a PSF image table can be held in a separate ROM, and the PSF memory 6 can hold difference data with respect to the PSF image data and a ratio coefficient. When the difference data and the ratio coefficient have a small capacity as compared with the image data, the capacity of the PSF memory 6 included in the camera module 1 can be made small.
The estimation approximation method of the PSF data is not limited to the least square method, and other methods can be used. The PSF data can be held not in the PSF memory but in an external memory. An algorithm different from that of the Richardson-Lucy method can be used as the algorithm of image restoration. The controller 26 can calculate the aberration components in advance, and not the PSF data but the aberration components can be held in the PSF memory.
A fourth embodiment of the present invention is explained with reference to
The PSF data held in the PSF memory 6 includes the measured PSF data and design PSF data. The design PSF data is PSF data indicating a PSF acquired from a design value of the imaging lens 2. The measured PSF data is PSF data indicating a PSF acquired from captured data acquired by capturing the adjustment chart by the camera module 1.
A PSF estimating unit (estimating unit) 7 estimates other pieces of PSF data (PSF data of other areas) based on the measured PSF data and the design PSF data held in the PSF memory 6. The image correcting unit (restoration unit) 8 performs correction such as a restoring process of image data using the PSF data. The image memory 10 stores therein and holds the corrected image data. A process of storing the PSF data in the PSF memory 6, a process of correcting images by the image correcting unit 8, and a process of estimating the PSF data of other areas by the PSF estimating unit 7 are explained later.
The process of storing the PSF data in the PSF memory 6 included in the camera module 1 is explained.
That is, the PSF memory 6 holds the PSF data of two areas of a central part and a peripheral part of the image sensor 4 as the measured PSF data. The PSF data acquired from area Q1 is designated as the measured PSF data p1 and the PSF data acquired from area Q5 is designated as measured PSF data p5. Accordingly, the measured PSF data p1 and p5 can be read and used any time as far as the PSF memory 6 is accessed. The pieces of the measured PSF data p1 and p5 are acquired by capturing the adjustment chart by the camera module 1 already assembled, that is, the camera module 1 having an individual difference. Accordingly, the measurement data p1 and p5 reflect the individual difference of the camera module 1.
The correcting process of the image data captured by the camera module 1 is explained next. The camera module 1 first captures a subject (Step S51). Accordingly, a raw image can be acquired as the image data of the subject. The image correcting unit 8 performs noise reduction with respect to the raw image (Step S52). The image correcting unit 8 performs the restoring process with respect to the raw image. As shown in
The estimating process of the PSF data p2 to p4 and p6 to p9 of other areas performed by the PSF estimating unit 7 is explained next. The PSF estimating unit 7 estimates the PSF data p2 to p4 and p6 to p9 of other areas based on the estimated PSF data p1 and p5 and the design PSF data. The PSF estimating unit 7 acquires a magnitude of the basic aberration amount such as spherical aberrations, coma-aberrations, and astigmatism, which are the third-order aberrations, and a magnitude of the out-of-focus amount from the measured PSF data p1 and p5. Because spherical aberrations, coma-aberrations, and astigmatism have directionality, these elements are considered as independent components. As shown in
The PSF correcting unit 7 also acquires the magnitude of the basic aberration amount such as spherical aberrations, coma-aberrations, and astigmatism, which are the third-order aberrations, and the magnitude of the out-of-focus amount in the same manner from the design PSF data. These independent components are designated as aberration components D3 to D8 (Step S62). When there is no manufacturing error of the imaging lens 2 or no assembly error of the camera module 1, A(i) and D(i) match each other. However, because it is generally difficult to eliminate the manufacturing error and the assembly error, A(i) and D(i) are different in the camera module 1.
Therefore, the PSF estimating unit 7 performs a polynomial approximation by using the least square method with respect to aberration components A3 to A8 and D3 to D8 (Step S63). The PSF estimating unit 7 calculates the PSF data in the areas T2 to T4 and T6 to T9, that is, the PSF data p2 to p4 and p6 to p9 of other areas by using the approximating polynomial (Step S64). The PSF estimating unit 7 obtains a change rate of the aberration components from the measurement value and the design value, and estimates the PSF data in the entire surface of the image sensor 4 based on the change rate. The image restoring process at Step S53 is performed by using the PSF data p2 to p4 and p6 to p9 of other areas.
An effect of restoration depends on the image restoration algorithm; however, for example, an image restoration method according to the Richardson-Lucy method can be used. Accordingly, an image close to an actual image having less optical strain or blur can be acquired. Even if there is a manufacturing error of the imaging lens 2, because an image close to the actual image can be acquired by the restoring process explained in the first embodiment, the manufacturing accuracy required for the imaging lens 2 can be suppressed to reduce the manufacturing cost.
The measurement data p1 and p5 and the design PSF data need only to be held in the PSF memory 6, the capacity of the PSF memory 6 can be made small as compared with a case that all pieces of the PSF data in the entire surface of the image sensor 4 are held, and the parts cost can be suppressed.
The adjustment chart 24 is a point image chart including point images; however, it is not limited thereto, and the adjustment chart 24 can be a chart in which the captured data in the respective areas Q1 to Q9 can be used as the PSF data or a chart in which the pieces of captured data are images having a strong correlation with the PSF data.
The PSF data acquired from area Q5 which is the central part of the adjustment chart 24 and the PSF data acquired from area Q1 which is the peripheral part thereof are designated as the measured PSF data; however, it is not limited thereto, and arbitrary two points can be selected.
The adjustment chart 24 is divided into nine areas of 3×3; however, it can be divided into M×N areas of M rows by N columns (M and N are integers). As M×N becomes larger, the accuracy of the restoring process can be improved.
The dividing direction is not limited to a matrix shape, and can be a curvilinear coordinate, for example. The number of divisions does not depend on the dividing direction, and can be arbitrary two points. The PSF data is not limited to image data. For example, a PSF image table can be held in a separate ROM, and the PSF memory 6 can hold difference data with respect to the PSF image data and a ratio coefficient. When the difference data and the ratio coefficient have a small capacity as compared with the image data, the capacity of the PSF memory 6 included in the camera module 1 can be made small. The PSF memory 6 can hold aberration components calculated in advance as the PSF data.
The PSF data can be held not in the PSF memory 6 in the camera module 1 but in an external memory. An algorithm different from the Richardson-Lucy method can be used as the algorithm of image restoration. The estimation method of the PSF data is not necessarily limited to the least square method.
A modification of the fourth embodiment is explained next. In this modification, when estimating the PSF data of other areas, the PSF estimating unit 7 subdivides the areas T1 to T9 of the image sensor 4, to divide the entire surface of the image sensor 4 into 6561 areas of 81×81.
That is, the PSF estimating unit 7 estimates the PSF data in each area other than the area t1 in the area T1 and in each area other than the area t5 in the area T5 as the PSF data of other areas. The PSF estimating unit 7 also estimates the PSF data in the subdivided respective areas of the areas T2 to T4 and T6 to T9 as the PSF data of other areas. The estimation method of the PSF data of other areas is identical to that of the fourth embodiment, and thus detailed explanations thereof will be omitted.
Generally, even in the same area T1, the PSF is different for each area. In the fourth embodiment, the measured PSF data p1 is adopted as the PSF data representing the area T1, and the measured PSF data p1 is applied to the entire area T1 to restore the image data. On the other hand, in this modification, the controller 26 further subdivides the area T1, and estimates the PSF data for each subdivided area to acquire the estimated PSF data of other areas. Because the restoring process is performed by using the PSF data of other areas, the restoring process can be performed by using the PSF data corresponding to the area, and more accurate restoring process can be realized. In this modification, the PSF estimating unit 7 divides the entire area into 6561 areas of 81×81; however, the entire area can be divided into I×J areas of I rows by J columns (I and J are integers). As I×J becomes larger, the accuracy of the restoring process can be improved.
A fifth embodiment of the present invention is explained with reference to the drawings. Constituent elements identical to those in the above embodiments are denoted by like reference numerals and redundant explanations thereof will be omitted. In the fifth embodiment, the PSF estimating unit 7 acquires the basic aberration amount such as spherical aberrations, coma aberrations, and astigmatism, which are third-order aberrations, and the out-of-focus amount by performing the Fourier transform with respect to the measured PSF data p1 and p5 and the design PSF data.
Because spherical aberrations, coma-aberrations, and astigmatism have directionality, these elements are considered as independent components. Like in the fourth embodiment, respective aberration components are designated as A3 to A8 and D3 to D8. The PSF estimating unit 7 performs a polynomial approximation by using the least square method with respect to aberration components A3 to A8 and D3 to D8. The PSF estimating unit 7 calculates a wavefront aberration amount by using the approximating polynomial based on the corrected coefficient. The PSF estimating unit 7 calculates the PSF data of other areas by performing inverse Fourier transform with respect to the calculated wavefront aberration amount. The PSF estimating unit 7 can calculate the PSF data in the areas T2 to T4 and T6 to T9 of the areas obtained by dividing the image sensor 4 into nine areas, or can further subdivide the areas T1 to T9 to calculate the PSF data in each subdivided area similarly to the modification of the fourth embodiment as the PSF data of other areas. The restoring process of the image data can be performed by using the measured PSF data and the PSF data of other areas similarly to the fourth embodiment.
In the fifth embodiment, because the measured PSF data and the design PSF data are Fourier-transformed for obtaining the aberration components, respective aberration components A3 to A8 and D3 to D8 can be handled as the complete independent components, and the estimation accuracy of the PSF data of other areas can be improved. Accordingly, more accurate restoring process can be realized.
A modification of the fifth embodiment is explained next. In this modification, measured PSF data p5 and design PSF data in the area T5, which is the central part of the image sensor 4, are held in the PSF memory 6, and the PSF data in the area T1, which is the peripheral part of the image sensor 4, is not held.
The PSF estimating unit 7 acquires the wavefront aberration amounts such as a basic aberration amount such as spherical aberrations, coma aberrations, and astigmatism, which are third-order aberrations, and the out-of-focus amount by performing the Fourier transform with respect to measured PSF data p5 and the design PSF data. Because spherical aberrations, coma-aberrations, and astigmatism have directionality, these elements are considered as independent components. Like in the fourth embodiment, respective aberration components are designated as A3 to A8 and D3 to D8. The PSF estimating unit 7 performs a polynomial approximation by using the least square method with respect to aberration components A3 to A8 and D3 to D8. The PSF estimating unit 7 calculates the wavefront aberration amount by using the approximating polynomial based on the corrected coefficient. The PSF estimating unit 7 calculates the PSF data of other areas by performing inverse Fourier transform with respect to the calculated wavefront aberration amount. The PSF estimating unit 7 can calculate the PSF data in the areas T2 to T4 and T6 to T9 of the areas obtained by dividing the image sensor 4 into nine areas, or can further subdivide the areas T1 to T9 to calculate the PSF data in each subdivided area as the PSF data of other areas, similarly to the modification of the fourth embodiment. The restoring process of the image data can be performed by using the measured PSF data and the PSF data of other areas similarly to the fourth embodiment.
In the modification of the fifth embodiment, because the measured PSF data and the design PSF data are Fourier-transformed for obtaining the aberration components, respective aberration components A3 to A8 and D3 to D8 can be handled as the complete independent components, and the estimation accuracy of the PSF data of other areas can be improved. Accordingly, more accurate restoring process can be realized. The PSF data of other areas can be estimated without performing the Fourier transform.
Further, the pieces of data stored in the PSF memory 6 are one piece of measured PSF data p5 and the design PSF data. Therefore, the capacity of the PSF memory 6 can be made small as compared with a case that two pieces of the PSF data p1 and p5 are held, and the parts cost can be further suppressed.
The data held in the PSF memory is not limited to measured PSF data p5 in the area T5, which is the central part of the image sensor 4, and can be PSF data in one area selected from the peripheral the areas T1 to T4 and T6 to T9.
A sixth embodiment of the present invention is explained with reference to
The estimating process of PSF data of other areas and the restoring process of the image data using the measured PSF data and the design PSF data held in the PSF memory are the same as those in the above embodiments, and thus detailed explanations thereof will be omitted.
As described above, the accuracy of the PSF data of other areas estimated by the PSF estimating unit 7 can be improved by selecting the area having the largest change rate of the design value and the measured value as the one area. Further, because the change rate is calculated for each camera module 1 to select the one area, an area suitable for estimating the PSF data of other areas of the camera module 1 can be set as the one area. Accordingly, a difference in accuracy of the restoring process of image data by the camera module 1 can be suppressed, thereby enabling to provide the camera module 1 with less difference in quality. Further, because a difference in quality decreases, the yield can be improved further. In the sixth embodiment, one area is selected. However, two or more areas can be selected and PSF data of these areas can be held as the measured PSF data.
A seventh embodiment of the present invention is explained with reference to
The lens barrel 32 includes the imaging lenses 32a and 32b, an aperture 32c, a lens holder 32e, and an infrared filter 33. The imaging lenses 32a and 32b have a function of imaging an image of a subject reasonably with respect to the image sensor 34 arranged at a predetermined position. In the seventh embodiment, the imaging lens includes two lenses. The number of lenses constituting the imaging lens is not limited to two, and one lens or three or more lenses can constitute the imaging lens. The aperture 32c has a function of controlling an amount of light entering the image sensor 34 to an appropriate amount. The infrared filter 33 has a function of not transmitting unnecessary long wavelengths other than a visible range. The imaging lenses 32a and 32b and the aperture 32c are fixed to the lens holder 32e by an adhesive 32d. That is, the lens holder 32e functions as a holding unit that holds the imaging lenses 32a and 32b and the aperture 32c. A screw thread is formed on an outer circumference of the lens holder 32e.
The circuit board 46 with the barrel holder 46c includes an image sensor 46a, a circuit board 46b electrically connected via, for example, wire bonding, the barrel holder 46c that shields unnecessary light from outside and fixes the lens barrel 32, and a circuit pad 46d to be used for connection with an external circuit. A screw thread is formed on an inner circumference of the barrel holder 46c. Although not shown, a memory that holds the measured PSF data and the like can be arranged on the circuit board 46b, or can be provided outside of the circuit board 46b and connected with the image sensor via the circuit pad 46d.
The lens holder 32e has such a configuration that the lens holder 32e is screwed into the inside of the barrel holder 46c and fixed. That is, the camera module 31 can adjust a distance between the lens holder 32e and the barrel holder 46c by adjusting a screw-in depth of the lens holder 32e with respect to the barrel holder 46c. Accordingly, an optical distance, that is, a distance between the imaging lenses 32a and 32b and the image sensor 46a can be adjusted so that the image of the subject is imaged (focused) reasonably with respect to the image sensor 46a by the imaging lenses 32a and 32b.
An assembly device 30 assembles the camera module 31 having the circuit board 46 with the barrel holder 46c in which the lens barrel 32 and the image sensor 46a are provided. The assembly device 30 includes a light irradiating unit 30b that irradiates light to the camera module 31, and an optical chart 30a that confirms whether reasonable imaging has been performed at the time of screwing the lens holder 32e in the barrel holder 46c.
The optical chart 30a includes a black and white periodic pattern, for example, provided by the ISO. Light irradiated from the light irradiating unit 30b is transmitted through the optical chart 30a and imaged on the image sensor 46a. At this time, by adjusting the screw-in depth of the lens holder 32e with respect to the barrel holder 46c so that the black and white periodic pattern is imaged (focused) reasonably with respect to the image sensor 46a by the imaging lenses 32a and 32b, the camera module 31 can be assembled so that a reasonable imaging state can be achieved.
The camera module 31 is not limited to one having the configuration explained in the seventh embodiment. For example, the aperture may not be provided or a shutter may be provided, or vise versa. Methods other than a screwing method of the lens barrel can be used as a method of fixing the member, and for example, an adhesive can be used for the fixing. Further, a connection method with an external circuit is not limited to the method explained in the seventh embodiment. While the configuration of the camera module has been explained in the seventh embodiment, the seventh embodiment can be applied to any module in which an image is formed on an image sensor.
Additional advantages and modifications will readily occur to those skilled in the art. Therefore, the invention in its broader aspects is not limited to the specific details and representative embodiments shown and described herein. Accordingly, various modifications may be made without departing from the spirit or scope of the general inventive concept as defined by the appended claims and their equivalents.
| Number | Date | Country | Kind |
|---|---|---|---|
| 2009-017045 | Jan 2009 | JP | national |
| 2009-017046 | Jan 2009 | JP | national |
