Methods and systems for blending line image data streams from a film scanner are disclosed. In one embodiment, a method is provided including receiving multiple data streams from line scan sensors. An overlap position may then be initially selected, which forms an overlap position between two of the data streams. A difference measure may then be calculated between the two data streams within the overlap area. The overlap positions may then be iteratively altered between a plurality of overlap positions, and additional difference measures may be computed for each overlap position. A blending position may then be selected from the plurality of overlap positions, which may correspond to the overlap position with the smallest difference measure. The data streams may then be blended at the selected blending position.

An image reading device includes: an FB glass; a sensor module having a light source and a plurality of sensors; and an image processor that generates correction data to be used for shading correction and performs the shading correction on image signals by using the correction data. The plurality of sensors is arranged in a main scanning direction and is configured to form an image signal on a single line. The image processor acquires second black data by causing the plurality of sensors to acquire an image signal of a reference sheet placed on the FB glass with the light source turned on, and generates black correction data based on the second black data. By performing the shading correction by using the black correction data, the image processor corrects density unevenness, in an image, caused by interference between image signals from the plurality of sensors.

An image processing apparatus includes an acquisition unit configured to acquire a reference image serving as a reference printing result and a target image serving as a printing result to be inspected, a correction unit configured to correct the target image based on a paper white area of each of the reference image and the target image so that a paper white color of the paper white area of the target image matches a paper white color of the paper white area of the reference image, wherein the paper white area is determined based on a positional displacement between the reference image and the target image, and an inspection unit configured to inspect the printing result by comparing the corrected target image with the reference image.

A system and method evaluate defects in printed images. A target image, which has been captured of a printed image, is processed to identify defects, where present, which do not occur in a source image from which the printed image was generated. A trained classification model predicts a defect class for respective regions of the target image, each of the defect classes being drawn from a predefined set of defect classes. For at least one of the identified defects, a measure of severity of the defect is determined, such as a size of the defect. A decision on the acceptability of the printed image is made, based on the measure of severity of the at least one defect and the predicted defect class of a respective one of the regions in which the defect occurs.

In a method and device for extracting joint line of shoe, a contact end of a contouring tool is provided to contact a joint contour of a shoe sample, an encoder is provided to generate a plurality of first trajectory coordinate signals of the contact end while the contact end is moved along the joint contour, and a signal processor is provided to receive the first trajectory coordinate signals to create a digital joint line.

An information processing apparatus includes a processor configured to convert the values of pixels in a glossy region of process target image data by inputting the process target image data to a first learning unit that has been trained using, as first learning data, first read image data and second read image data so as to convert the first read image data into the second read image data. The glossy region corresponds to a glossy portion of a document. The first read image data include the glossy region, and are obtained by optically reading the document in a first reading environment in which the light amount of regularly reflected light from a learning data document acquired by an image sensor is less than a regularly reflected light amount threshold. The second read image data include the glossy region, and are obtained by optically reading the document in a second reading environment in which the light amount of the regularly reflected light acquired by the image sensor is equal to or more than the regularly reflected light amount threshold. The process target image data are obtained by optically reading a process target document in the first reading environment.

An image processing device acquires first and second image data respectively representing first and second images. The first image includes an object image showing a part of an object. The second image shows another part of the object. The first image and the object image respectively include an edge and an object-image edge with respect to a direction. The first image includes first pixels that is located between the edge and the object-image edge and not included in the first object image. The device selects one of arrangement methods according to a condition that the number of first pixels continuously arranged in the direction is larger than a prescribed level. The device determines a relative position between the first and second images using the selected method. The device generates arranged image data representing an arranged image in which the first and second images are arranged according to the relative position.

An image processing apparatus for detecting a singular point from image data having a plurality of pixel signals arranged in a two-dimensional manner, having a stochastic resonance processing unit configured to perform parallel steps in each of which a noise is added to and the result is subjected to binarization processing, synthesize the results of the parallel steps and output the result, with regard to each of the plurality of pixel signals; and a unit configured to detect the singular point based on the output signal value from the stochastic resonance processing unit for each of the plurality of pixel signals. The stochastic resonance processing unit performs the binarization processing on a pixel as a processing target among the plurality of pixel signals based on the pixel signal of the pixel as the processing target and a pixel signal of a pixel adjacent to the pixel as the processing target in a predetermined direction.

A method and program product includes capturing at least one image of an operations display of at least one peripheral device. The operations display at least presents information associated with a status encountered by the at least one peripheral device. The at least one image is communicated to at least one computing system. The at least one computing system is at least configured for processing the at least one image for extracting features of the at least one peripheral device, determining a model of the at least one peripheral from the extracted features, determining at least a status encountered by the peripheral device from the extracted features, and creating a resolution to the encountered status. The resolution to the encountered status is received from the at least one computing system and displayed.

A binary image of an input image is generated, and a character region within the binary image and a region surrounding each character are acquired as character segmentation rectangle information. A thinning process is executed on a region within the binary image which is identified based on the character segmentation rectangle information to acquire a thinned image. An edge detected image of the region identified based on the character segmentation rectangle information is acquired. Whether each character identified based on the character segmentation rectangle information is a character to be separated from a background by the binarization process or not is determined based on a result of a logical AND of the thinned image and the edge detected image.