Embodiments are generally related to rendering devices and techniques. Embodiments are also related to substrate edge sensors utilized in the context of rendering devices, such as printers, copiers and the like. Embodiments are additionally related to techniques for measuring a substrate edge signal.
Xerography represents one method of copying or printing documents, which can be performed by uniformly charging a charge retentive surface such as a xerographic photoreceptor belt (i.e., a type of substrate). This uniformly charged surface is then preferentially exposed in the desired image areas in order to create an electrostatic latent image of a desired original image. A developing material or a toner can be then deposited onto the latent image to form a developed image. The developed image is then transferred to a final substrate, such as paper. The residual developing material on the surface of the photoreceptor is then cleaned off and the photoreceptor belt surface is then recharged in preparation for the production of another image. Such a methodology is monochrome in nature due to the fact that each image is transferred directly from a photoreceptor to paper. Another approach to copying and/or printing involves the use of an intermediate belt system where one or more colors (e.g., four colors) can be transferred onto a belt and a single transfer to paper is then performed.
The mass of pigment (e.g., toner mass) on an intermediate transfer or photoreceptor belt can be sensed by a full width array (FWA) based sensing application. A belt edge sensor can be used to track the position of the belt with respect to a sensor. By tracking the position of the belt, it is possible to map the belt surface and utilize the map as part of a flat field algorithm to calibrate the FWA sensor signal. Many printing applications require the optical measurement of a toner mass on the belt surface, where the belt surface is not uniform.
A process sensor can be utilized to measure uniformity of the toner on the non-uniform belt substrate. The non-uniformities on the belt surface convolute with the measurement of the toner uniformity and thus the signal-to-noise ratio is reduced. The bare belt surface can be recorded and mapped ahead of time and this information can be used later to compensate the raw data, thereby increasing the signal-to-noise ratio. Such processing, however, requires a fairly precise registration between the measurement signal and the original bare-belt signal.
Once-around and belt-hole signals are commonly utilized to provide reference to a moving substrate such as a photoreceptor or a drum. The once-around signal can be used as a start trigger for data logging or capturing. In a xerographic application, the process patches and targets are often developed in an inter-document zone (IDZ) where the process sensor-sampling period is typically restricted to the IDZ. Thus, depending on the length of the intermediate transfer belt (ITB) and engine speed, there may be multiple inter-document zones for one complete belt revolution.
Typically, the intermediate transfer belts are seamless and the inter-document zone areas do not fall on the same region of the belt; rather, they propagate around the belt during a printing process. Hence, it is necessary to precisely register the data captured by a process sensor during the IDZ with an appropriate region of the bare-belt signal. Prior art printing applications typically utilize additional encoders or position sensors to track the belt movement and to register bare intermediate transfer belt signals to the signal measured for location of interest on the belt.
Based on the foregoing it is believed that a need exists for an improved method and system to register the bare intermediate transfer belt signal to the signal sensed in the region of interest (e.g. inter-document zone) without adding additional hardware.
The following summary is provided to facilitate an understanding of some of the innovative features unique to the embodiments disclosed and is not intended to be a full description. A full appreciation of the various aspects of the embodiments can be gained by taking the entire specification, claims, drawings, and abstract as a whole.
It is, therefore, one aspect of the present invention to provide for an improved rendering device, such as a printer.
It is a further aspect of the present invention to provide for the use of a belt edge signal sensor for image sensor phasing utilized in the context of a rendering device.
It is another aspect of the present invention to provide for an improved method and system for registering bare intermediate transfer belt signals to a signal detected in an inter-document zone (IDZ) region in the context of a rendering device.
The aforementioned aspects and other objectives and advantages can now be achieved as described herein. A system and method for measuring a belt edge signal for image sensor phasing is disclosed. An intermediate transfer belt edge signal can be effectively mapped by a belt edge sensor and a process sensor, and both can be recorded for at least one complete revolution. A belt edge signal sampled over an inter-document zone region of a belt, concurrently sampled by the process sensor, can be recorded in runtime. A cross-correlation can be applied between the bare intermediate transfer belt edge signal and the belt edge signal sensed in the inter-document zone. The cross-correlation algorithm returns a maximum peak value when the two signals are registered in-phase with one another.
The number of samples or time required to capture one complete revolution can be determined from the process speed, the sampling rate, and the actual length of the belt. The belt edge signal can be utilized to determine the belt length by finding the period of the belt edge data. An index of the maximum peak value can be determined in order to precisely align the bare intermediate transfer belt edge signal and the belt edge signal captured during the recording of the process sensor measurement of the patch of interest on the belt. The offset can then be utilized to determine the proper alignment of the bare belt and patch signals for the process sensor. Once properly aligned, a flat-fielding algorithm can be applied to remove artifacts and compensate for non-uniformities in the process sensor signal over the region of interest on the belt. If the process sensor sampling rate is not equal to the belt edge sensor-sampling rate, a proper conversion factor can be added to the cross-correlation algorithm.
The accompanying figures, in which like reference numerals refer to identical or functionally-similar elements throughout the separate views and which are incorporated in and form a part of the specification, further illustrate the embodiments and, together with the detailed description, serve to explain the embodiments disclosed herein.
The particular values and configurations discussed in these non-limiting examples can be varied and are cited merely to illustrate at least one embodiment and are not intended to limit the scope thereof.
a)-1(b) are provided as exemplary diagrams of data-processing environments in which the present invention may be embodied. It should be appreciated that
As depicted in
As depicted in
It can be appreciated that in some embodiments, the use of only one belt edge sensor and/or process sensor may be necessary, whereas in other embodiments multiple sensors may be desirable. Note that belt 170 constitutes one type of substrate in accordance with the present invention. Thus, a belt edge signal as discussed herein is merely one type of substrate edge signal. It can be appreciated that use of a belt such as belt 170 as discussed herein is presented for general illustrative purposes only. Other types of substrates and substrate edge sensors, and so forth, may be implemented in accordance with alternative embodiments.
The rendering device 108 generally includes the use of a belt edge determining circuit such as, for example circuits 112 and/or 113, which are utilized to adjust the test belt 170 to a desired testing position by adjusting the position of the movable roller 160. The process sensor 140 can be utilized to measure density and/or uniformity of the pigment (e.g., toner) on the non-uniform belt substrate 170. Note that process sensor 140 can be implemented as an optical full width array sensor (FWA) device or an optical point sensor such as an Enhanced Toner Area Coverage (ETAC) device, or other appropriate process sensor for one complete revolution of belt 170. Process sensor 140 may be a point sensor, an image sensor, and/or another similar type of suitable process sensor, depending upon design considerations. The belt edge sensors 135, 136 are utilized to detect the rotating belt edge 170 and generate signals of the belt edge position as output. The belt edge sensor 135 can be utilized to track the position of the belt 170. It is possible to map the belt edge by tracking the position of the belt 170 for at least one full revolution.
In general, a belt edge signal can be utilized as a quasi-encoder of the position of belt 170. Initially, on cycle-up, the output of the belt edge sensors 135 and/or 136 can be logged, along with the output of the process sensor 140 for one complete belt revolution. The number of samples or time required to capture one complete revolution of belt 170 can be determined from the process speed, the sampling rate, and the actual length of belt 170. Using the belt edge signal(s) generated by belt edge sensors 135, 136 along with data output from process sensor 140, one can also determine the belt length by determining the period of the belt edge data.
Once the belt-edge and bare-belt process sensor data for at least one complete revolution of the bare belt 170 is recorded, this data can be saved for subsequent lookup. In operation, as data is recorded from an IDZ zone or more generally, from any region of interest on belt 170 by a process sensor such as process sensor 140, the belt edge data is preferably recorded as well. By then carrying out a cross-correlation (e.g., see block 314 of
Following the process of the operation depicted at block 310, a belt edge signal and process sensor signal from a region of interest (e.g., IDZ area) sampled from any region of the belt 170 at run time by process sensor 140 and belt edge sensors 135, 136 can be recorded, as depicted at block 312. That is, the operation illustrated at block 312 involves recording both sensor signals (i.e., belt edge and process sensor) over the region of interest with the pigment (e.g., toner mass) present that is being measured. Thereafter, as illustrated at block 314, an operation can be processed in which a comparison algorithm (e.g., cross-correlation) is applied between the two belt edge sensor signals (i.e., bare belt/substrate and over the region of interest) to determine the proper offset for aligning the signals. The cross-correlation can thus be applied between the bare intermediate transfer belt edge signal and the belt edge signal sensed in the IDZ or appropriate region of interest on the substrate (e.g., belt 170). The cross-correlation algorithm returns a maximum peak value when the two signals are registered in-phase with one another. An index of the maximum peak value can be determined in order to precisely align the two sets of belt edge signals.
The offset determined as a result of processing the instructions indicated at block 314 can be used to align the two process sensor signals (i.e., recorded over the bare belt and the region of interest with pigment present), as illustrated next at block 316. Thereafter, as depicted at block 318, the phase aligned process sensor signals can be utilized to perform a flat-fielding (via a flat fielding algorithm) of the process sensor signal over the region of interest. This assists in eliminating non-uniformities of the bare substrate from the signal of interest (i.e., the process sensor response to the pigment on the belt). The flat-fielding algorithm can also be applied to remove artifacts and compensate for belt and/or substrate induced non-uniformities, as depicted at block 318.
Similarly, the period can be calculated by computing a lowest dominant frequency of the substrate edge signal from multiple revolutions. Next, as depicted at block 358, an operation can be implemented to begin recording belt edge sensor data. Thereafter, as illustrated at block 360, the substrate edge signal(s) can be recorded for 0.5 P. After 0.5 P, recording of the process sensor can also begin. While continuing to record the substrate edge signal(s), the process sensor bare belt is also recorded for the next 1.0 P, as indicated at block 362. At this point, the recording of the process sensor signal is terminated, but the belt edge sensor(s) are recorded for an additional 0.5 P, as described at block 364. The end result is a 2 P length vector of data for the belt edge sensor(s) and a 1.0 P length array of bare belt process sensor data.
Next, as indicated at block 366, an operation can be implemented to create and update a P length FIFO buffer of substrate edge data. Thereafter, as depicted at block 367, a region of interest having pigment (e.g., toner mass) on a surface of the substrate, can be measured and captured by both sensors. Following the process of the operation depicted at block 367, an operation can be implemented in which the two sets of substrate edge data are processed using a comparison or cross-correlation algorithm, as indicated by block 368. Next, as indicated at block 370, an operation can be implemented for determining the index of the maximum value of the cross-correlation output. Thereafter, as indicated at block 372, the two sets of process sensor data can be aligned. Finally, as illustrated at block 374, the flat-fielding algorithm can be applied, as described previously.
In general, the belt edge data of the belt edge sensor 135 for two revolutions can be recorded, as indicated by the method 400 depicted in
The index I can be found from the cross-correlation output, as shown at block 370 of
The index value I obtained from
Starting Sample: I−X−1 (2)
Ending Sample: I−1 (3)
If the values from equations (2) and (3) are both greater than 1.5 P, then exploiting periodicity, these values can be reduced by P so that the start and stop samples fall into the 0.5 to 1.5 P section where the bare belt map can be actually captured. If the starting sample is less then 1.5 P but the ending sample is not, then the samples from the result of equation (2) can be utilized to 1.5 P as the first part of the belt surface map and the remaining X−1.5 P samples from 0.5 P onward. By applying the I value and X value from
If the process sensor-sampling rate is not equal to the belt edge sensor-sampling rate then proper conversion factor must be added to the alignment algorithm.
The longer belt edge data provides a precise match independent of the noise, which does not dominate the signal. Further, by requiring a P length vector of edge data instead of edge data only when the process sensor 140 is sampling ensures that the cross-correlation algorithm does not err with too few samples where a pattern match cannot be established and the maximum value of a cross-correlation output is not distinct but flat.
It will be appreciated that variations of the above-disclosed and other features and functions, or alternatives thereof, may be desirably combined into many other different systems or applications. Also, that various presently unforeseen or unanticipated alternatives, modifications, variations or improvements therein may be subsequently made by those skilled in the art which are also intended to be encompassed by the following claims.