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Numerous research endeavors have employed the color selection procedure for a vast array of purposes. Detecting defects in fabrics, calculating the Microbial Community Color Index, analyzing digital color in facilitating fashion design processes and applying color to artworks, calculating canopy cover, and achieving other objectives have been the subject of research. This procedure necessitates intricate steps, intricate calculations, and lengthy computational time. In this study, a novel strategy for optimizing the color selection process using the Hadamard product technique is presented. The HSV color space is optimized by selectively selecting the desired colors and establishing threshold limits for each hue, saturation, and value component. The optimization results demonstrate that the desired colors are perfectly distinguished from other colors. Additionally, the proposed method employs a straightforward, step-by-step procedure that does not require feature extraction. In comparison to previous research, a remarkable increase in computational speed of 1,078.82 times faster has been observed. This improvement is achieved by multiplying each element of the HSV matrix resulting from color selection as opposed to the HSV matrix without selection. This study&#x2019;s findings are applicable not only to plant images but also to all cases requiring color selection under visible light conditions.

A Novel Method for Optimizing Color Selection Using The Hadamard Product Technique