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

Numerous research endeavors have employed color selection procedures for a vast array of purposes. Detecting defects in fabrics, calculating the Microbial Community Color Index, analyzing digital color to facilitate fashion design processes, applying color to artworks, calculating canopy cover, and achieving other objectives have been the subject of research. This procedure requires intricate steps, calculations, and a 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. The faster computational speed observed in this study during the color selection process has the potential to be used in unmanned aerial vehicles to select green plants or ripe fruits.This study’s findings are applicable not only to plant images but also to all cases requiring color selection under visible light conditions.