Abstract: A lens testing system may have a test pattern source that generates a test pattern of light. A lens may have a lens surface that reflects the test pattern of light. A digital camera system may capture an image of the reflected test pattern of light. Computing equipment may perform image processing operations to evaluate the captured image of the reflected test pattern. The test pattern may contain a known pattern of test elements such as a rectangular array of spots or test elements of other configurations. During image processing operations, the computing equipment may analyze the reflected version of the spots or other test elements to measure characteristics of the lens such as radius of curvature, whether the lens contains flat regions, pits, or bumps, lens placement in a support structure, and other lens performance data. The computing equipment may compare the measured lens data to predetermined criteria.

Abstract: Methods and systems for use in calibrating imaging data, are provided that include using a calibration array to generate a test pattern. The calibration array can emit a test pattern having geometric, temporal, and electromagnetic characteristics. The collected data can be compared with the geometric, temporal and electromagnetic characteristics to determine an error factor that can then be used in analyzing the collected data.

Abstract: The present disclosure discloses a method and an apparatus for measuring response curve of an image sensor. The method comprises: taking at least one photograph of a Grey Scale card with an image sensor to be measured, wherein the photograph comprises a plurality of greyscale image blocks; calculating relative exposure values for each greyscale image block respectively corresponding to the greyscale blocks of the Grey Scale card; plotting a plurality of reference points based on pixel values of pixel points within each greyscale image block and the relative exposure values, and executing an interpolation calculation based on the reference points to obtain a response curve of the image sensor.

Abstract: A method for providing a mapping from apparent color to actual color for an image capture device including capturing an image of a reference color chart having a plurality of color patches using the image capture device, wherein each color patch has an associated reference color, measuring the apparent color of the plurality of color patches in the captured image, selecting a plurality of control points representing different hue values within a circular hue space, determining an angular offset for each control point such that the distance between a transformed apparent color and the reference color for each color patch is minimized, the angular offset representing a hue correction, wherein interpolation of the angular offsets for the control points provides a mapping from apparent color to actual color for the image capture device.

Abstract: There is provided a method for configuring a set of image capturing settings of a camera for a first scene condition type currently viewed by the camera. The method comprises detecting the first scene condition type; instructing the camera to acquire a plurality of test images, each test image corresponding to a set of image capturing settings; receiving input relating to a selected test image, and storing the set of image capturing settings corresponding to the selected test image as the configured set of image capturing settings for the first scene condition type to be used by the camera upon future detections of the first scene condition type.

Abstract: There is provided an image processing apparatus including multiple imaging units included in a stereo camera, the multiple imaging units configured to photograph a chart pattern including a pole, and a correction parameter calculation unit configured to calculate a correction parameter that corrects a gap between the multiple imaging units, based on the pole and a pattern included in the chart pattern photographed by the multiple imaging units.

Abstract: A calibration device applied to an image capture system includes a support unit and a plurality of display pattern generation units. The plurality of display pattern generation units are pivoted to the support unit. Each display pattern generation unit of the plurality of display pattern generation units includes a plurality of marks, the plurality of marks are used for generating a display pattern corresponding to the display pattern generation unit, the plurality of marks are not overlapped each other in the display pattern, and a plurality of display patterns of the plurality of display pattern generation units are also not overlapped each other. The plurality of display patterns are used for forming a calibration pattern applied to geometric calibration of the image capture system.

Abstract: A theoretical motion blur amount is calculated. A static state image is acquired. For each of the plurality of shutter speed values, a bokeh amount at the boundary between different color areas in each of a plurality of the static state images that have been acquired is measured as a bokeh offset amount. A vibrated state image while the camera is being vibrated with its image stabilization function being ON is acquired. A bokeh amount at the boundary between different color areas in each of the plurality of vibrated state images that have been acquired is measured as a measured comprehensive bokeh amount. And an evaluation value indicating the performance of the image stabilization function of the camera is calculated based on the theoretical motion blur amount, the bokeh offset amount, and the measured comprehensive bokeh amount.

Abstract: A captured image including a preferential calibration index arranged in an exclusive region in a first plane and a non-preferential calibration index arranged in a common region is obtained. First, the coordinate position of the preferential calibration index is detected, and then the coordinate position of the non-preferential calibration index is calculated based on the positional relationship with the detected preferential calibration index. A homography between a captured-image surface of the image surface and the first plane is calculated based on the actual coordinate positions and the calculated coordinate positions representing the coordinates of at least four points, and camera calibration is performed using the homography.

Abstract: The present disclosure relates to color calibration chart acquisition. In an example, a video acquired by an imaging device may be processed. The video may be analyzed to automatically detect a reproduction of a color calibration chart. Upon detection of a reproduction of the color calibration chart, it may be determined whether color calibration chart reproduction quality is within a selected quality threshold. Upon determining that color calibration chart reproduction quality is not within a selected threshold, user feedback may be provided, via the imaging device, to dynamically guide the user to make adjustments in the video acquisition in order to obtain a color calibration chart reproduction within the selected quality threshold.

Abstract: Imaging devices may include processing circuitry, a lens, and an array of image sensor pixels and reference pixels. The array may receive direct image light and stray light from the lens. The image sensor pixels may include clear color filter elements and the reference pixels may include opaque color filter elements. The opaque color filter elements may block direct image light from being captured by the reference pixels. The image sensor pixels may generate pixel values in response to the direct image light and the stray light whereas the reference pixels may generate reference pixel values in response to the stray light. The processing circuitry may mitigate stray light effects such as local flare and veiling glare within the imaging system by adjusting the pixel values based on the reference pixel values. The imaging system may be calibrated in a calibration system for generating stray light calibration data.

Abstract: Systems and methods for calibrating an array camera are disclosed. Systems and methods for calibrating an array camera in accordance with embodiments of this invention include the capturing of an image of a test pattern with the array camera such that each imaging component in the array camera captures an image of the test pattern. The image of the test pattern captured by a reference imaging component is then used to derive calibration information for the reference component. A corrected image of the test pattern for the reference component is then generated from the calibration information and the image of the test pattern captured by the reference imaging component. The corrected image is then used with the images captured by each of the associate imaging components associated with the reference component to generate calibration information for the associate imaging components.

Abstract: Systems and methods for calibrating a 360 degree camera system include imaging reference strips, analyzing the imaged data to correct for pitch, roll, and yaw of cameras of the 360 degree camera system, and analyzing the image data to correct for zoom and shifting of the cameras. Each of the reference strips may include a bullseye component and a dots component to aid in the analyzing and correcting.

Abstract: Embodiments of the invention relate to digital imaging, and in particular, systems methods, and devices for testing target field illumination characteristics. Certain embodiments include a main unit that includes a controller configured to control timing indicators on a front surface of the main unit and light sensor modules attached to the periphery the front surface. The main unit can be configured to accept an image quality test chart. The light sensors can be configured to be coupled to the periphery of the image quality test chart or coupled to extended wired or wireless connections to provide flexible field of view placement. The display includes LED or LCD timing indicators.

Abstract: A theoretical motion blur amount is calculated. A static state image is acquired. For each of the plurality of shutter speed values, a bokeh amount at the boundary between different color areas in each of a plurality of the static state images that have been acquired is measured as a bokeh offset amount. A vibrated state image while the camera is being vibrated with its image stabilization function being ON is acquired. A bokeh amount at the boundary between different color areas in each of the plurality of vibrated state images that have been acquired is measured as a measured comprehensive bokeh amount. And an evaluation value indicating the performance of the image stabilization function of the camera is calculated based on the theoretical motion blur amount, the bokeh offset amount, and the measured comprehensive bokeh amount.

Abstract: The present disclosure relates to color calibration chart acquisition. In an example, a video acquired by an imaging device may be processed. The video may be analyzed to automatically detect a reproduction of a color calibration chart. Upon detection of a reproduction of the color calibration chart, it may be determined whether color calibration chart reproduction quality is within a selected quality threshold. Upon determining that color calibration chart reproduction quality is not within a selected threshold, user feedback may be provided, via the imaging device, to dynamically guide the user to make adjustments in the video acquisition in order to obtain a color calibration chart reproduction within the selected quality threshold.

Abstract: A memory unit stores as conversion information which is derived based on a correction coefficient which provides, in a predetermined allowable range from a minimum value, a sum of a norm of a difference between a color difference of a correction target color and a target color which is a target of correction of the correction target color and a correction color obtained by correcting the correction target color using the correction coefficient, and a norm of the correction coefficient to which a predetermined weight coefficient is applied. A color correcting unit converts a color of each pixel of an image captured by an image capturing unit based on the conversion information.

Abstract: Methods, systems and software are disclosed for automated Measurement of Video Quality parameters. The system includes a static Test Pattern provided either in form of a Test Pattern File, converted via a standard playout device (test source) into analog or digital test signal and supplied to the input of a System Under Test, or in form of a Reflectance Chart installed before the front-end device of the System Under Test, such as TV camera. The system also includes a video capture device connected to the back-end device of the System Under Test, e.g. to the output of system decoder/player. A Video Quality Analyzer processes the captured video data and generates a detailed Analysis Report.

Abstract: The present disclosure related to acquisition of color calibration charts. In at least some examples herein, an image of a calibration color chart is processed. A lighting condition of the color calibration chart may be automatically determined.

Abstract: Embodiments are directed towards determining within a digital camera whether a pixel belongs to a foreground or background segment within a given image by evaluating a ratio of derivative and deviation metrics in an area around each pixel in the image, or ratios of derivative metrics across a plurality of images. For each pixel within the image, a block of pixels are examined to determine an aggregate relative derivative (ARD) in the block. The ARD is compared to a threshold value to determine whether the pixel is to be assigned in the foreground segment or the background segment. In one embodiment, a single image is used to determine the ARD and the pixel segmentation for that image. Multiple images may also be used to obtain ratios of a numerator of the ARD, useable to determine an extent of the foreground.

Abstract: A three-dimensional coordinate position of a calibration device is determined. Further, a code is emitted to an image capture device. The code indicates the three-dimensional coordinate position of the calibration device. In addition, an image of light emitted from the calibration device is captured. The light includes the code. An image capture device three-dimensional coordinate position of the calibration device is calibrated according to the real world three-dimensional coordinate position of the calibration device indicated by the code.

Abstract: Methods, systems and software are disclosed for automated Measurement of Video Quality parameters. The system includes a static Test Pattern provided either in form of a Test Pattern File, converted via a standard playout device (test source) into analog or digital test signal and supplied to the input of a System Under Test, or in form of a Reflectance Chart installed before the front-end device of the System Under Test, such as TV camera. The system also includes a video capture device connected to the back-end device of the System Under Test, e.g. to the output of system decoder/player. A Video Quality Analyzer processes the captured video data and generates a detailed Analysis Report.

Abstract: Embodiments of the invention relate to digital imaging, and in particular, systems methods, and devices for testing target field illumination characteristics. Certain embodiments include a main unit that includes a controller configured to control timing indicators on a front surface of the main unit and light sensor modules attached to the periphery the front surface. The main unit can be configured to accept an image quality test chart. The light sensors can be configured to be coupled to the periphery of the image quality test chart or coupled to extended wired or wireless connections to provide flexible field of view placement. The display includes LED or LCD timing indicators.

Abstract: A method for calibrating a camera and a display monitor is provided. The method includes identifying a parameter for optimization, assigning to a test color a target color relevant to the parameter, repeatedly performing, two or more times, a set of steps, determining a direction and timing of color divergence for the target color from obtained images, and adjusting the parameter based on the direction and rate of color divergence for the target color. The set of steps includes instructing the display monitor to display the test color on a portion of the display monitor, obtaining an image captured by the camera while the display is executing the instruction, and reassigning, to the test color, a color obtained from a portion of the image in which the portion of the display monitor was captured. The obtained image includes the portion of the display monitor.

Abstract: A calibration plate and a method for calibrating image capturing devices are provided. The calibration plate includes: a plate having a front face and a rear face; a plurality of calibration patterns formed at the front face of the plate, arranged in a regular manner, and used to calibrate image distortions, lens aberrations, and image center positions for the image capturing devices; and a plurality of graphically encoded patterns formed at the front face of the plate, the graphically encoded patterns being different from each other, and the graphically encoded patterns having information providing the positions of the calibration patterns.

Abstract: The present disclosure relates to a sensor network including a plurality of nodes, each node having a directional sensor, a communication module, and a processor configured to receive local measurements of a calibration object from the directional sensor, receive additional measurements of the calibration object from neighboring nodes via the communication module, estimate an initial set of calibration parameters in response to the local and additional measurements, receive additional sets of calibration parameters from neighboring nodes via the communication module, and recursively estimate an updated set of calibration parameters in response to the additional sets of calibration parameters. Additional systems and methods for calibrating a large network of camera nodes are disclosed.

Abstract: A plurality of homography operators define respective mappings between pairs of coordinate spaces, wherein the coordinate spaces include a coordinate space of a first visual sensor, a virtual coordinate space, and a coordinate space of a second visual sensor. Calibration between the first and second visual sensors is provided using the plurality of homography operators.

Abstract: Blur-calibration of an imaging sensor includes moving a known target pattern across the field-of view (FOV) of the imaging sensor to present the target pattern across different frames at different pixel phases. The known target pattern comprises a plurality of point-like objects with fixed relative positions in which at least one point-like object has a different focus position. Frames of images of the moving target pattern as seen in the FOV of the imaging sensor are captured to sample point-like objects at different focus positions and generate a multi-focal image data output, which may be subsequently processed to generate data products at different focus positions from a high-resolution composite image generated from the captured frames.

Abstract: A testing device for a camera, in particular of driver assistance systems in a motor vehicle, including a mount for a camera and at least two light sources for emitting test light toward the camera, the mount and at least one of the at least two light sources being situated fixed in relation to one another with respect to their relative location and position, and a control device which is configured to activate the at least two light sources in such a way that in chronological sequence one light source is switched on and the at least one other light source is switched off. Also described is a related testing method for a camera and a testing system.

Abstract: A system for determining one or more camera calibration parameters is disclosed. The system comprises a processor and a memory. The processor is configured to: a) provide a first pattern for display on a display screen; b) receive a first image from a camera viewing the display screen; c) provide a second pattern for display on the display screen; and d) receive a second image from the camera viewing the display screen. The relative position of the display screen and the camera are the same as when the first image was captured using the camera. The processor is further configured to determine an image location which is a projection of a known physical location on the display screen by using at least in part a first feature identified in the first image and a second feature identified in the second image and determine one or more calibration parameters based at least in part on the determined image location. The memory is coupled to the processor and configured to provide the processor with instructions.

Abstract: An optical analysis method is provided for judging whether a lens and a sensing element of an image pickup device are parallel with each other. The method utilizes a tested image pickup device and a standard image pickup device to shoot an object at the same fixed shooting position to acquire a standard image frame and a tested image frame. According to the difference between the position coordinate value or the area of at least one mark of the standard image frame and the tested image frame, the method can judge whether the tested lens and the tested sensing element of the tested image pickup device are parallel with each other.

Abstract: The invention relates to a method for estimating a defect in an image-capturing system (I), which produces, with regard to any first image (I), representing any scene (S), a variation in the field of a characteristic of the first image, having an order of magnitude that is statistically lower than a variation in the field of said characteristic added by the scene. The method comprises: calculating, in at least a first portion of the field of the first image, a measurement (?(I)) related to said characteristic of the first image, an estimative magnitude (?) of said defect, depending on the calculated measurement and having a variation having the same order of magnitude as the variation in the field of said characteristic of the first image produced by said defect.

Abstract: There is provided an image processing apparatus including multiple imaging units included in a stereo camera, the multiple imaging units configured to photograph a chart pattern including a pole, and a correction parameter calculation unit configured to calculate a correction parameter that corrects a gap between the multiple imaging units, based on the pole and a pattern included in the chart pattern photographed by the multiple imaging units.

Abstract: An image-capturing device and a projection automatic calibration method of a projection device are provided. The image-capturing device includes an image sensing device, a lens, a processing unit and a storage unit. The lens is configured to image a calibration pattern on the image sensing device. The processing unit is configured to issue a projection calibration requirement and analyze the calibration pattern imaged on the image sensing device to obtain information relating to the calibration pattern, and the processing unit is further configured to convert imaging coordinates of the calibration pattern imaged on the image sensing device into projecting coordinates of the projection device by executing a calibration driving program to establish a coordinate conversion table. The storage unit is configured to store the calibration driving program and the coordinate conversion table.

Abstract: This invention provides a system and method for auto-regulation of parameters a vision system camera and/or associated illumination of objects imaged by the camera using a plurality of differentiated gain (multi-gain) settings on the camera's image sensor to determine the gain value producing the most-readable image. The image (having the best characteristics) acquired using multiple gain settings can be read for information as a discrete gain image and/or the camera parameters (e.g. global gain and/or global exposure time) can be uniformly set across the pixel array to the best values for acquisition of a subsequent, higher sampled image. This image is then read (e.g. decoded) for information contained within any identified features of interest (e.g. found IDs).

Abstract: Imaging device calibration methods, imaging device calibration instruments, imaging devices, and articles of manufacture are described. According to one embodiment, an imaging device calibration method includes emitting light for use in calibration of an imaging device, providing an emission characteristic of the light, sensing the light using an image sensor of the imaging device, generating sensor data indicative of the sensing using the image sensor, and determining at least one optical characteristic of the imaging device using the generated sensor data and the emission characteristic for use in calibration of the imaging device, and wherein the at least one optical characteristic corresponds to the image device used to sense the light.

Abstract: A pattern includes a spatial configuration of color codes. Each color code is a unique configuration of colors selected from a number of basis colors. The color codes each include the same number of colors.

Abstract: The present application relates to a high precision method for calibrating and removing distortion from a lens, and more particularly, a method for calibrating and removing distortion by arranging sensor readings to compensate for its presence and simultaneously optimize the resulting image magnification for best image quality.

Abstract: Embodiments of a system and method for blur-calibration of an imaging sensor using a moving constellation are generally described herein. In some embodiments, blur-calibration of an imaging sensor includes moving a known target pattern across the field-of view (FOV) of the imaging sensor to present the target pattern across different frames at different pixel phases. Frames of images of the moving target pattern as seen in the FOV of the imaging sensor are captured to generate image data output. The image data output may be subsequently processed to generate data products representative of a shape of a point-spread function (PSF) from a high-resolution composite image generated from the captured frames. A chopper modulation may be applied to the moving target sequence and separate chopper-open and chopper-closed composite images are created. The PSF may be determined based on the difference between the chopper-open and chopper-closed composite images.

Abstract: A method is provided for positioning an image sensor having a light receiving plane within a camera and a system is provided for identifying the position of an image sensor. The method comprises projecting a first group of substantially parallel light beams representing a first predetermined pattern onto the light receiving plane of the image sensor at an angle of incidence, projecting a second group of substantially parallel light beams representing a second predetermined pattern onto the light receiving plane of the image sensor at an angle of incidence, registering positions on the light receiving plane of the image sensor where the light beams are detected by the image sensor, generating adjustment information based on the registered positions, indicating if the present position of the image sensor is an erroneous position or not, and adjusting the position of the image sensor based on the adjustment information.

Abstract: A method of calibrating a brightness value measured by a camera with an amount of light received by the camera includes creating a series of measurements, wherein for each measurement the amount of light received at an image plane in the camera is controlled to be a known ratio of two opposed irradiance values: a high irradiance value and a low irradiance value. Each ratio is correlated with the brightness value measured by the camera. A function is obtained describing the correlation.

Abstract: Methods and systems for use in calibrating imaging data, are provided that include using a calibration array to generate a test pattern. The calibration array can emit a test pattern having geometric, temporal, and electromagnetic characteristics. The collected data can be compared with the geometric, temporal and electromagnetic characteristics to determine an error factor that can then be used in analyzing the collected data.

Abstract: A camera system (10) includes: a camera (12) that obtains a test image (200); and an image processor (30). The image processor (30): analyzes said test image (200) to detect an object (22) appearing in the test image (200); determines a location where the detected object (22) appears in the test image (200); compares the determined location with a reference location; and determines if the camera (12) is one of properly aligned or misaligned based upon a result of said comparison.

Abstract: A color calibration card (1) for digital photography with a maximum of 40 calibration fields, each exhibiting a color in a color space according to CIE 1976 (L*, a*, b*) D50 2°, wherein a first group with at least 3 calibration fields (4G1, 4G2, 4G3) exhibits green colors having an a value within the range of ?30 to ?60 and a b value within the range of +10 to +30, a second group (4B1, 4B2, 4B3) exhibits blue colors having an a value within the range of ?20 to ?20 and a b value within the range of ?30 till ?60, a third group (4R1, 4R2, 4R3) exhibits red colors having an a value within the range of +40 to +60 and a b value within the range of ?5 to +30, and wherein the respective calibration fields in each group (4G1, 4G2, 4G3; 4B1, 4B2, 4B3; 4R1, 4R2, 4R3) exhibit colors for which the values in at least one of a or b differ by at least 5 units from the corresponding values for the other calibration fields in the group.

Abstract: An image correction device includes a test chart, an image capturing module, an image separating module, a processing module, a first calculating module, a second calculating module, and a correction module. The image capturing module includes an image sensor for capturing an image of the test chart. The image includes two second circular black spots. The image separating module separates the image, thus obtaining a channel image. The processing module is for binarizing the channel image, thus obtaining a binary image of the channel image. The first calculating module calculates coordinates of the centers of the two second spots of the binary image. The second calculating module calculates a rotated angle of the image. The correction module inputs the rotated angle into the image sensor so that the image sensor corrects the image.

Abstract: Imaging systems, imaging device analysis systems, imaging device analysis methods, and light beam emission methods are described. According to one aspect, an imaging device analysis method includes receiving initial light comprising a plurality of wavelengths of light, filtering some of the wavelengths of the initial light forming a plurality of light beams comprising different wavelengths of light, after the filtering, optically communicating the light beams of the different wavelengths of light to an imaging device, receiving the light beams using the imaging device, and analyzing the imaging device using light, wherein the light beams comprising the different wavelengths of light are emitted beams after the receiving.

Abstract: In one embodiment, the present invention is a method and apparatus for measuring the focus performance of a camera and lens combination. One embodiment of a test target for measuring a focus performance of a camera and lens combination includes a target body, the target body displaying a pattern including: a primary pattern covering a portion of the target body and a secondary pattern superimposed over a portion of the primary pattern, the secondary pattern being aligned along an edge of the target body. The test target also includes a ruler positioned adjacent to the edge of the target body, a ruler positioned adjacent to the edge of the target body, such that the secondary pattern directly abuts a zero line of the ruler.

Abstract: Provided is a television camera using a solid-state imaging device, wherein color signal adjustment between TV cameras can be performed easily and quickly without relying on the level of skill of an operator. The serial digital signal of a TV camera (a master) acting as the standard for color signal adjustment is directly input into another TV camera (a slave) that adjusts the color signal, and the image level of each channel of the slave is automatically adjusted in a manner such that the image level of each channel of the master corresponds with that of the slave.

Abstract: An image-capturing device and a projection automatic calibration method of a projection device are provided. The image-capturing device includes an image sensing device, a lens, a processing unit and a storage unit. The lens is configured to image a calibration pattern on the image sensing device. The processing unit is configured to issue a projection calibration requirement and analyze the calibration pattern imaged on the image sensing device to obtain information relating to the calibration pattern, and the processing unit is further configured to convert imaging coordinates of the calibration pattern imaged on the image sensing device into projecting coordinates of the projection device by executing a calibration driving program to establish a coordinate conversion table. The storage unit is configured to store the calibration driving program and the coordinate conversion table.

Abstract: A camera module under test is signaled to capture an image of a target. A group of pixels of the image that represent portions of several objects in the target are low pass filtered and then analyzed to compute a pixel distance between different subgroups of pixels that represent portions of the different objects. The computed pixel distance is then converted into a true distance using a predetermined math relationship that relates a pixel distance variable with a true distance variable.