Recognition of characters in document images using morphological operation

Abstract

In this paper, we deal with the problem of document image rectification from image captured by digital cameras. The improvement on the resolution of digital camera sensors has brought more and more applications for non-contact text capture. It is widely used as a form of data entry from some sort of original paper data source, documents, sales receipts or any number of printed records. It is crucial to the computerization of printed texts so that they can be electronically searched, stored more compactly, displayed on-line, and used in machine processes such as machine translation, text-to-speech and text mining. Unfortunately, perspective distortion in the resulting image makes it hard to properly identify the contents of the captured text using traditional optical character recognition (OCR) systems. In this work we propose a new technique; it is a system that provides a full alphanumeric recognition of printed or handwritten characters at electronic speed by simply scanning the form. Optical character recognition, usually abbreviated as OCR is the mechanical or electronic conversion of scanned images of handwritten, typewritten or printed text into machine-encoded text. OCR software detects and extracts each character in the text of a scanned image, and using the ASCII code set, which is the American Standard Code for Information Interchange, converts it into a computer recognizable character. Once each character has been converted, the whole document is saved as an editable text document with a highest accuracy rate of 99.5 per cent, although it is not always this accurate. The basic idea of Optical Character Recognition (OCR) is to classify optical patterns (often contained in a digital image) corresponding to alphanumeric or other characters.