An example color resource is generated. A source color from a first color space is converted to a corresponding greyscale color in a greyscale color space. The greyscale color includes a first luminosity amount. A black channel amount is adjusted to a depletion color from a second color space to form a target color in the second color space. The depletion color corresponds with a transformation of the source color into the second color space. The depletion color includes a second luminosity amount, and adjusting the black channel includes matching the second luminosity amount in the target color with the first luminosity amount.

A method, apparatus, and system for identifying objects based on grayscale images in the operation of an autonomous driving vehicle is disclosed. In one embodiment, one or more first color images are received from a camera mounted at an autonomous driving vehicle (ADV). One or more first grayscale images are generated based on the one or more first color images, which comprises converting each of the one or more first color images into one of the first grayscale images. One or more objects in the one or more first grayscale images are identified based on a pre-trained grayscale perception model. A trajectory for the ADV is planned based at least in part on the identified one or more objects. Control signals are generated to drive the ADV based on the planned trajectory.

An apparatus configured to generate image data represented in achromatic color from input image data and output the generated image data to a printer includes a controller. The controller is configured to replace color information of an object included in the input image data with an achromatic signal value, determine, based on an achromatic signal value corresponding to color information of a pixel of interest in the input image data, whether the pixel of interest satisfies a predetermined condition, and perform enhancement processing on the color information of the pixel of interest in a case where the pixel of interest is determined not to satisfy the predetermined condition.

A computer, which executes a color machine driver for outputting print data generated by an application program for generating the print data to a color image forming apparatus, accepts an interlocking setting, which is a setting for whether a color setting which is a setting for causing the color image forming apparatus to execute color printing or monochrome printing is interlocked with the application program. In case that the color setting is set not to be interlocked with the application program in the interlocking setting, when the color setting in the color machine driver is a color setting that causes the color image forming apparatus to execute the monochrome printing, the computer causes the application program to generate print data for the color image, and executes a monochrome image forming process for converting the color image into a monochrome image.

An apparatus includes a setting unit and a control unit. The setting unit performs a first print setting indicating a poster printing function that divides a single piece of image data into a plurality of pieces of image data and generates print jobs, and a second print setting indicating a correction function for correcting calculated gray values when an image processing apparatus converts a plurality of pieces of color image data to grayscale, based on a number of colors acquired from each of the plurality of pieces of color image data. The control unit restricts the setting unit from performing the first print setting and the second print setting. In a state where one of the first print setting and the second print setting is performed by the setting unit, the control unit controls the setting unit not to perform the other print setting.

In an image data conversion device, color image data is represented in gray scale, a histogram of brightness values is created for the gray-scaled image data, it is determined based on the created histogram which image pattern of a plurality of image patterns the gray-scaled image data is classified into, a range subjected to gamma correction and a range fixed to at least one of a minimum value and a maximum value of gray scale are set for each image pattern, and image data conversion including the gamma correction is performed on the gray-scaled image data.

A non-transitory computer-readable medium stores computer-readable program instructions configured to, when executed, cause an information processing device to receive a scan instruction to cause an image scanner to perform image scanning of a document sheet, the scan instruction including a scan setting indicating whether to perform monochrome scanning or color scanning, receive image data generated by the image scanning of the document sheet according to the scan instruction, obtain base color information representing whether black is set as a base color in an OS of the information processing device, determine whether an image represented by the image data includes a text, and display the image in a black-white inverted manner, when the scan instruction includes the scan setting indicating to perform the monochrome scanning, the base color information represents that black is set as the base color, and it is determined that the image includes a text.

An auto-rotation module having a single-layer neural network on a user device can convert a document image to a monochrome image having black and white pixels and segment the monochrome image into bounding boxes, each bounding box defining a connected segment of black pixels in the monochrome image. The auto-rotation module can determine textual snippets from the bounding boxes and prepare them into input images for the single-layer neural network. The single-layer neural network is trained to process each input image, recognize a correct orientation, and output a set of results for each input image. Each result indicates a probability associated with a particular orientation. The auto-rotation module can examine the results, determine what degree of rotation is needed to achieve a correct orientation of the document image, and automatically rotate the document image by the degree of rotation needed to achieve the correct orientation of the document image.

The APPARATUSES, METHODS AND SYSTEMS FOR A VIDEO REMOTE DEPOSIT CAPTURE PLATFORM (hereinafter “RDC-Video”) provides a platform for remote deposit by obtaining images of a check from streaming video captured by a video camera, wherein the RDC-Video transforms captured check images and/or entered check deposit information inputs via RDC-Video components into deposit confirmation outputs. For example, in one embodiment, a user may employ a personal computer connected to a web camera, and/or a smartphone with a built-in camera to initiate the remote deposit by holding a check in front of the camera, and the RDC-Video may capture images of the check and send them to a financial institution for deposit processing.

Apparatus, methods and systems of object recognition are disclosed. Embodiments of the inventive subject matter generates map-altered image data according to an object-specific metric map, derives a metric-based descriptor set by executing an image analysis algorithm on the map-altered image data, and retrieves digital content associated with a target object as a function of the metric-based descriptor set.