Bandingkan kaedah

	Segmentasi Watershed	Analisis Kontur
Bidang	Penglihatan Komputer	Penglihatan Komputer
Keluarga	Machine learning	Machine learning
Tahun asal	1979	1985
Pengasas	Serge Beucher and Christian Lantuéjoul	Satoshi Suzuki and Keiichi Abe
Jenis	Morphological image segmentation	Shape and contour analysis
Sumber perintis	Meyer, F. (1994). Topographic distance and watershed lines. Signal Processing, 38(1), 113–125.	Suzuki, S., & Abe, K. (1985). Topological structural analysis of digitized binary images by border following. Computer Vision, Graphics, and Image Processing, 30(1), 32–46.
Alias	Watershed transform, Water shedding segmentation	Edge-based contours, Boundary analysis
Berkaitan	5	5
Ringkasan	Watershed segmentation is a morphological image processing technique that automatically segments an image into distinct regions by treating image intensity as a topographic landscape where each object corresponds to a valley. Introduced by Beucher and Lantuéjoul in 1979 and refined by Meyer, the watershed algorithm is particularly effective for separating touching or overlapping objects.	Contour analysis is the process of detecting and analyzing the boundaries of objects in images by identifying connected edges and extracting shape information. The Suzuki-Abe algorithm provides an efficient method for finding contours in binary images, enabling shape-based object classification and segmentation.