#Image Segmentation with Watershed Algorithm – OpenCV Python|Hostbox cse

This video is very useful for learn the concept of Image Segmentation .

Lecture by Nagarajan.S, M.E (CSE) ,(Ph.D)
SRMIST

Image segmentation is a fundamental computer vision task that involves partitioning an image into meaningful and semantically homogeneous regions. The goal is to simplify the representation of an image or make it more meaningful for further analysis. These segments typically correspond to objects or regions of interest within the image.

Watershed Algorithm

The Watershed Algorithm is a classical image segmentation technique that is based on the concept of watershed transformation.The segmentation process will take the similarity with adjacent pixels of the image as an important reference to connect pixels with similar spatial positions and gray values.

Working of Watershed Algorithm

The watershed algorithm divides an image into segments using topographic information. It treats the image as a topographic surface, identifying catchment basins based on pixel intensity. Local minima are marked as starting points, and flooding with colors fills catchment basins until object boundaries are reached. The resulting segmentation assigns unique colors to regions, aiding object recognition and image analysis.