GUI-Based Image Segmentation Demonstration

This article presents an image segmentation demonstration developed using MATLAB's Graphical User Interface (GUI). The demonstration encompasses three fundamental segmentation techniques: thresholding methods, edge detection algorithms, and region-based approaches. Thresholding methods provide a straightforward yet effective way to separate images into foreground and background components, often implemented using functions like graythresh() for automatic threshold calculation and imbinarize() for binary image conversion. Edge detection techniques, commonly employed through operators such as Sobel, Prewitt, or Canny (using edge() function), excel at identifying object boundaries and contours within images. Region-based methods operate on pixel similarity principles, utilizing algorithms like region growing or watershed transformation (via watershed() function) to partition images into homogeneous regions. Through these implemented methods, users can gain deeper insights into image segmentation processes and effectively apply these techniques to various real-world scenarios, with the GUI providing interactive parameter adjustment and immediate visual feedback on segmentation results.