Abstract
This study presents a robust image processing algorithm for accurately counting sarees/T-shirts placed on retail shop shelves. The proposed algorithm employs k-means clustering for color quantization, a technique that reduces the number of colors in an image. Through iterative refinement of centroids, the algorithm effectively categorizes objects into distinct clusters, achieving accurate counts. This research offers a valuable approach to automate inventory management in retail settings, enhancing efficiency and precision.
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