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When watching sports on screen, fans recognize inconsistencies in their team colors. ColorNet is a patent-pending artificial intelligence (AI) technology that ingests live video, adjusts each frame pixel-by-pixel, and outputs color corrected video in real-time ensuring accurate brand colors. In this study, ColorNet is demonstrated using Clemson University orange, Pantone 165. The patent- pending technology developed for this study uses machine learning techniques to identify regions of an image with incorrect color and adjust only those specified pixels to maintain consistent brand specifications. Unlike alternative approaches, ColorNet performs color correction on-the-fly and pixel-by-pixel, automatically adjusting to scene changes that impact how color is perceived. With the creation of two prototype devices, ColorNet has demonstrated the ability to perform real-time color correction for displays. The resulting color adjustments focus only on regions in the image that should match brand color specifications without negatively impacting surrounding colors.
Automatically color-corrects digital images for various software applications such as on-the-fly video color correction.
Circumvents human error when color correcting while constantly adjusting for negative caused by lighting or weather changes on the display of colors on screen.
Targets specific color values and adjusts only the targeted colors pixel-by-pixel without shifting any other surrounding colors in the frame.