Extract RGB Pixel Color Data From Multiple Images Software
Extract RGB Pixel Color Data From Multiple Images Software is a reliable program designed to determine the HEX code assigned to each pixel in a picture. Simply load the images you wish to test and the software can return individual reports containing the position of each pixel and the afferent web color code.
A reliable tool for color identification
The software can scan each pixel of an image and apply the color pick technique in order to identify the tinge assigned to the certain pixel. The software can repeat the process for each pixel contained in the file, as well as for all the images in the list. The colors identified by the application are marked in two modes.
Thus, each color is expressed as RGB values and HEX codes. The report file contains three columns, first one representing the position of the pixel in the matrix, while the other two indicate the color assigned to the specific pixel.
The software extracts the colors and identifies their digital indicator
RGB represents a color work space in which the tinges are expressed in the amount of the base colors contained within. Just like in the case of the color spectrum, each nuance is obtained by combining three base colors. In the RGB case, the colors are red, green and blue.
The HEX code contains six digits that indicate the color based on brightness, hue, contrast, saturation and spectrum area. This hexadecimal code is mostly used in the online environment, in order to express a specific color.
Batch file processing and detailed reports
Extract RGB Pixel Color Data From Multiple Images Software can handle multiple images at the same time, but it returns individual reports for each file. Moreover, you can manage the list of images by adding separate photos or load an entire folder. You may specify the output location, then watch as the software processes the files in a quick manner. The application is reliable and it can identify hundreds or thousands of colors in the selected photo. The speed of the process is reduced, however, in case of large images.
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