Watershed Segmentation Algorithm
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Watershed-based image segmentation is a fundamental technique in image processing that partitions images into distinct regions to facilitate better understanding and manipulation of visual data. This method finds applications across various domains including computer vision, medical imaging, and autonomous driving systems. In watershed segmentation, the image is treated as a topographic surface where pixel intensity or color values represent elevation levels. The algorithm identifies watershed lines or boundaries by simulating flooding processes from regional minima, effectively separating different regions. This approach enables precise object identification and extraction from images, leading to more accurate image analysis and processing. Implementation typically involves gradient magnitude calculation, marker-controlled watershed transformation, and region merging techniques to prevent over-segmentation issues commonly associated with this algorithm.
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