An information processing apparatus includes a processor configured to: obtain plural images each including any of plural objects; and determine, based on an analysis result regarding the plural objects in the plural images, according to which of two or more objects, among the plural objects, included in an image the image is corrected.

An image forming apparatus includes: a scanner to read each of a first output product serving as a model and a second output product output from the image forming apparatus; a memory that stores a color conversion lookup table to be used when color conversion is performed from a RGB color system into a CMYK color system; and circuitry to correct the color conversion lookup table based on a number of pixels and an amount of change per hue, using read information on the first output product, and re-correct the corrected color conversion lookup table, using read information on the second output product.

Certain examples described herein relate to halftone level adjustment for Neugebauer Primaries (NPs). In certain examples, halftone levels for NPs are obtained for a halftone for printing an image. It is determined whether the halftone corresponds to a line or an area fill. The halftone levels may be adjusted in response to these levels exceeding a printing attribute threshold. The printing attribute threshold may be dependent on whether the halftone corresponds to a line or an area fill. The image may then be printed using the adjusted halftone levels.

A color image of a target is captured by a color sensor in an imaging reader. A color image processing pipeline processes the captured color image with a plurality of color image processing components to display the image of a target with high fidelity. One or more of the components are bypassed to decode the image of a symbol target to prevent degradation of reader performance.

A pattern for camouflage and a method for making the pattern. The method includes taking photographic images from the perspective of the selected animal or bird. In one embodiment, the photographic image can be taken from above so as to create a finite background within the selected environment. In another embodiment, the pattern is adapted to be seamlessly repeatable across a surface. The method includes placing desired harvested abstracts into the photographic scene to obtain the overall desired effect of the camouflage pattern including color, composition, depth and repeat. The method also includes taking multiple photographs of the same scene from the same exact spot focusing on different parts of the photographic scene to add clarity to certain portions of the images, enhance depth, and reach desired color palate. The method includes adjusting the color of objects, including water within the photographic scene, to reflect true color of objects absent outside conditions.

An image forming apparatus includes a table generating unit. The table generating unit determines whether a target-value Voronoi region and a measured-value Voronoi region are identical or not. The table generating unit sets an output color value associated with a print position where the target-value Voronoi region and the measured-value Voronoi region are identical in the second color conversion table as the output color value associated with a specific input color value in the first color conversion table. The table generating unit sets the output color value associated with the print position where the target-value Voronoi region and the measured-value Voronoi region are different in the second color conversion table as a color value that is a color value in the hue plane and is different from the output color value associated with the specific input color value in the first color conversion table.

In a case where a sample color is outside a color reproduction range of an image forming apparatus, there arises an issue that an adjustment target color cannot be brought close to a user-desired color. An image forming apparatus includes a generation unit configured to cause a printing unit to print a plurality of colors close to an acquired sample color and generate a color conversion table based on a user-selected color among the plurality of printed colors in a case where it is determined that the acquired sample color is outside a color reproduction range of the image forming apparatus, whereas in a case where it is determined that the acquired sample color is not outside the color reproduction range, the generation unit generates a color conversion table without causing the printing unit to print the plurality of colors close to the sample color.

In this print method, assuming that the number of stacking of ink layers in a thickest portion in a thickly-piled portion is N, in a histogram preparation step ST2, a histogram of luminance values of grayscale image data prepared in an image data preparation step ST1 is prepared, and in luminance value range setting steps ST3 to ST10, a luminance value of predetermined gradations of the histogram is divided into N and N luminance value ranges are set. In the luminance value range setting steps ST3 to ST10, a division position of the luminance value of the predetermined gradations is adjusted while the histogram displayed on a predetermined display is checked.

In a pixel of a part where two objects are superimposed, pixel values of the objects are compared to thereby set an attribute of the pixel to an attribute of one of the objects.

Examples are described for applying different settings for image capture to different portions of image data. For example, an image sensor can capture image data of a scene and can send the image data to an image signal processor (ISP) and a classification engine for processing. The classification engine can determine that a first object image region depicts a first category of object, and a second object image region depicts a second category of object. Different confidence regions of the image data can identify different degrees of confidence in the classifications. The ISP can generate an image by applying a different settings to the different portions of the image data. The different portions of the image data can be identified based on the object image regions and confidence regions.