Embodiments of the present disclosure provide an image calibration method, an image forming apparatus, and a storage medium. The method includes outputting a calibration image in response to a calibration instruction, where the calibration image includes a calibration pattern and a calibration mark; according to the calibration mark of the calibration image, determining whether a calibration event corresponding to the calibration image matches a calibration event corresponding to a current calibration operation, or determining whether a calibration event type corresponding to the calibration image matches a calibration event type corresponding to a current calibration operation; and performing image calibration according to the calibration pattern in the calibration image if the calibration event corresponding to the calibration image matches the calibration event corresponding to the current calibration operation, or if the calibration event type corresponding to the calibration image matches the calibration event type corresponding to the current calibration operation.

An image forming apparatus including a plurality of sheet feeding cassettes includes a control unit. The control unit performs control. In a case where a predetermined condition is satisfied during execution of a print job to print image data, the control unit performs control to execute interruption processing of a correction job to print a correction patch. The control unit performs control to determine, from the plurality of sheet feeding cassettes, a sheet feeding cassette to be used for the correction job based on information on the sheet feeding cassette used for the print job.

A system and method provide for automated evaluation of reference point pairs. For each of a set of reference point pairs in an input color space, a straight line connecting the reference points is sampled to generate a set of sampled points. Each of the set of sampled points in the input color space is converted to a sampled point in an output color space. For each of a set of color separations in the output color space, discontinuities are identified, based on the set of sampled points in the output color space. Candidate reference point pairs are identified in the set of reference point pairs for which at least one discontinuity is identified. The candidate reference point pairs can be validated by printing test sweeps, which are each derived from a respective set of sampled points in the output color space, and identifying contour artifacts in the printed test sweeps.

A minimum luminance value of a display luminance information is larger than a minimum luminance value of a print luminance information. And in a conversion, a luminance value of a dark region of input image data is converted to a luminance value of a dark region of output image data such that a contrast of a dark region that includes the minimum luminance value of the print luminance information becomes closer to a contrast of a dark region that includes the minimum luminance value of the display luminance information.

An ophthalmic image processing apparatus includes a processor. The processor acquires a first image as a color fundus image, and corrects a pixel value of at least any color component in the first image, based on color gamut information for specifying a predetermined color gamut to be applied to a color fundus image, to generate a color gamut-corrected image.

In some examples, a system detects a highlighted area in an image content, the highlighted area including a portion of the image content, and a highlighting mark that highlights the portion of the image content. The system applies a color adjustment process in the highlighted area, wherein the color adjustment process comprises adjusting a color of the highlighted area comprising the portion of the image content highlighted by the highlighting mark, and wherein the adjusting of the color of the highlighted area comprises adjusting color values of plural color components in a first color space.

An image processing apparatus for converting color data into gray data extracts an object included in the color data in a page, and determines, based on color information and position information on a first object and a second object extracted, whether at least one of the first object and the second object is to be a target of conversion of a color value of the color data into a gray value with improved discriminability. The image processing apparatus controls to convert the color value of the object into a gray value by a conversion targeting all color values, or into a gray value with the improved discriminability, based on the determination whether or not to be the target of conversion.

A color printing system includes a printing device and other components that use color printing resources, such as calibration and ICC profiles, to complete color printing operations. These color printing resources are used for a large number of paper types stored in a paper catalog. The paper types can be further placed into paper groups within the paper catalog. The paper groups may be formed by assigning new papers into the paper catalog to those having paper types with existing calibration data and ICC profiles. These relationships are shown in a paper catalog map. The print shop can use the paper catalog map for selling paper types, providing different capabilities for paper types, and other information. The paper catalog map also may be used to select a paper type from a primary paper type and a secondary paper type.

Color filters are used for color images obtained using imaging devices such as conventional image sensors. Imaging elements with color filters are sold, and an appropriate combination of the imaging element and a lens or the like is incorporated in an electronic device. Only providing a color filter to overlap a light-receiving region of an image sensor reduces the amount of light reaching the light-receiving region. An imaging system of the present invention includes a solid-state imaging element without a color filter, a storage device, and a learning device. Since the color filter is not included, colorization is performed on obtained monochrome image data (analog data), and coloring is performed using an AI system.

Examples described herein relate to automatic identification and transformation of a color region. A user can identify a region of a video frame or image that corresponds to a color region that is to be segmented. A color region can include one or more colors that appear to be approximately a uniform color. For one or more video frames, gamma correction can be applied to frames of the video. One or more frames of a video can be mapped to two color spaces. For each pixel in an image, a determination is made if the pixel has the same color as that of the identified region based on each of the at least two color spaces identifying the pixel as the color. The color region can be identified throughout a video and transformed to another color to aid in video editing.