Image Color Clustering Segmentation
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Image color clustering segmentation is a graphical processing technique that partitions images based on color characteristics and displays them using RGB features. This method employs clustering algorithms (typically K-means clustering) to group pixels with similar color properties into distinct segments. The implementation generally involves extracting RGB values from image pixels, applying dimensionality reduction or color space conversion when necessary, and using clustering algorithms to classify pixels into predefined color groups. This technique enables better identification of different color regions within images, facilitating subsequent analysis and processing tasks such as object recognition and image quantization. The algorithm outputs segmented regions that can be visualized through color-coded masks or boundary overlays.
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