This study was undertaken to develop machine vision-based raisin detection technology. Supervised color image
segmentation using a Permutation-coded Genetic Algorithm (GA) identifying regions in Hue-Saturation-Intensity (HSI)
color space (GAHSI) for desired and undesired raisin detection was successfully implemented. Images were captured to
explore the possibility of using GAHSI to locate desired raisin and undesired raisin regions in color space
simultaneously. In this research, images were processed separately using three segmentation method, K-Means clustering
in L*a*b* color space and GAHSI for single image, GA for single image in Red-Green-Blue (RGB) color space
(GARGB). The GAHSI results provided evidence for the existence and separability of such regions. When compared
with cluster analysis-based segmentation results, the GAHSI method showed no significant difference.
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