MATLAB Implementation Source Code for Watershed Image Segmentation Method in Digital Image Processing

The watershed image segmentation method implemented in MATLAB is one of the commonly used techniques in digital image processing. This algorithm performs pixel-level segmentation by dividing an image into distinct regions, facilitating the identification and separation of different objects within the image. The method leverages both grayscale information and gradient data from the image, determining pixel labels based on differences between grayscale values and gradient magnitudes to produce final segmentation results. MATLAB serves as a powerful programming tool for implementing the watershed segmentation algorithm. Through MATLAB coding, developers can follow the algorithmic steps and principles to process digital images and obtain corresponding segmentation outcomes. The implementation typically involves key functions such as gradient calculation (using imgradient or similar functions), distance transform computation, and marker-controlled watershed transformation to prevent over-segmentation. For those interested in understanding watershed image segmentation in digital image processing and seeking to implement it using MATLAB, this source code provides a practical resource to learn and comprehend the specific implementation process of this method. The code demonstrates proper handling of gradient computation, marker selection, and watershed transformation to achieve effective region-based image segmentation.