Design and Development of robust OCR system for hand filled form in Office Automation

Abstract

Hand-filled forms are a ubiquitous means of information collection, yet their manual processing remains labor-intensive and error-prone. In this paper we proposed a novel approach to completely automate the processing of template based hand filled form and store the recognized data in central database. The proposed framework combines image processing techniques for form segmentation and a convolution neural network model, for accurate character recognition. By seamlessly integrating these components, the proposed approach streamlines the transition from handwritten content to digital data, reducing manual effort and potential errors.