Bimodal Method: A Simple Thresholding Segmentation Technique

The bimodal method is a widely used and simple thresholding segmentation technique. Its fundamental principle involves determining an appropriate segmentation threshold by analyzing the gray-level histogram of an image. Specifically, when the histogram exhibits two distinct peaks, the gray-level value at the valley between these peaks is selected as the threshold for segmentation. This method is intuitive and applicable to various image processing tasks. For instance, in image segmentation, the bimodal method can effectively separate foreground and background elements. By applying threshold-based segmentation, we can extract regions of interest and facilitate subsequent image processing and analysis. The implementation typically involves generating a histogram using functions like imhist in MATLAB or cv2.calcHist in OpenCV, followed by identifying peak positions through peak detection algorithms and calculating the minimum value between them. Consequently, the bimodal method holds significant practical value in the field of image processing.