Letter Recognition Implementation Using MATLAB

In this project, we implement letter recognition functionality primarily using MATLAB. The system accurately identifies and classifies input letters through image processing and machine learning techniques. This project serves as an excellent graduation design topic, demonstrating proficiency in key areas such as image preprocessing, feature extraction, and classification algorithms. The implementation typically involves several key components: image preprocessing functions (imread, imresize, rgb2gray) for input normalization, feature extraction methods (like HOG or contour analysis) for character representation, and classification algorithms (such as SVM or neural networks using MATLAB's Classification Learner app) for accurate letter identification. The project structure allows for easy extension to recognize digits or additional characters by modifying the training dataset and adjusting classification parameters. This scalability makes the system more comprehensive and practical for real-world applications. These implementation details and expansion possibilities should help enhance your graduation project's technical depth and practical value.