Program Source Code for Character Segmentation Using Projection Method

This article provides a detailed explanation of the program source code for character segmentation using the projection method. In this program, we first perform image preprocessing on the input image, which includes grayscale conversion, binarization, and noise removal steps. The grayscale conversion typically utilizes weighted average methods (e.g., using cv2.COLOR_BGR2GRAY in OpenCV), while binarization applies thresholding techniques such as Otsu's method to distinguish characters from the background. Subsequently, we employ the projection method for character segmentation by calculating horizontal and vertical projections to determine character boundaries. The horizontal projection involves summing pixel values row-wise to identify text line separations, while the vertical projection sums column-wise to isolate individual characters. Finally, the segmented characters are utilized for subsequent recognition or processing tasks. Through this program, users can better understand and apply the projection method in character segmentation, improving both the accuracy and efficiency of character segmentation. Key functions may include projection curve analysis for peak/valley detection and boundary coordinate extraction algorithms.