An Optical Character Recognition Software Built on MATLAB Platform

An optical character recognition software developed on the MATLAB platform. This specialized tool is engineered to convert printed or handwritten characters into editable digital text through a multi-stage processing pipeline. The system implements advanced image preprocessing techniques including noise reduction, binarization using Otsu's thresholding, and skew correction algorithms to enhance input quality. Leveraging MATLAB's Computer Vision Toolkit, the software employs feature extraction methods (such as HOG descriptors) and machine learning classifiers (including SVM and CNN architectures) to achieve high recognition accuracy across diverse font styles and handwriting variations. The architecture supports batch processing capabilities through automated directory scanning and parallel computing functions, enabling efficient handling of multiple documents. Key technical features include multi-language support via Unicode-compatible character sets, adaptive segmentation algorithms for connected characters, and a GUI built with MATLAB App Designer for intuitive user interaction. The software integrates post-processing modules including spell-check dictionaries and layout preservation algorithms to maintain document structure integrity. Suitable for academic research, commercial applications, and personal use, this OCR solution significantly enhances productivity through its MATLAB-optimized image processing functions and customizable recognition parameters accessible via script-based configuration files.