EAN-13 Barcode Binarization with Full Processing Pipeline

In the MATLAB environment, you can implement a complete EAN-13 barcode processing pipeline comprising binarization, geometric correction, segmentation, and digit recognition. Using the Image Processing Toolbox, you can perform preprocessing operations such as contrast enhancement and noise reduction to improve recognition accuracy. For binarization, adaptive thresholding algorithms like Otsu's method or local thresholding can be implemented using the imbinarize function to handle varying illumination conditions. Geometric correction can be achieved through Hough transform line detection and affine transformations to rectify skewed barcode images. During segmentation, algorithms like connected component analysis and morphological operations ensure accurate and complete separation of individual bars and digits. Finally, digit recognition utilizes template matching or machine learning approaches where each character's binary pattern is compared against EAN-13 encoding standards. The implementation leverages key MATLAB functions including imread for image acquisition, imrotate for geometric correction, regionprops for segmentation analysis, and normxcorr2 for template-based recognition. This project provides comprehensive insights into digital image processing and pattern recognition methodologies while delivering practical barcode decoding capabilities.