UNVEILING COLORS: A K-MEANS APPROACH TO IMAGE-BASED COLOR CLASSIFICATION
Abstract
Color classification from images plays a pivotal role in computer vision applications, such as object recognition, image retrieval, and scene understanding. This research explores a novel approach to color classification utilizing the K-Means clustering algorithm. By partitioning image pixels into distinct color clusters, this technique facilitates accurate color recognition. The study showcases the methodology's effectiveness, shedding light on its potential in enhancing various image-based applications.
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