Same font and size may also have bold face character as well as normal one. There may be noise pixels that are introduced due to scanning of the image. Difference in font and sizes makes recognition task difficult if preprocessing, feature extraction and recognition are not robust. The verifying is done either randomly or chronologically by human Intervention. The recognizing process includes several complex algorithms and previously loaded templates and dictionary which are crosschecked with the characters in the document and the corresponding machine editable ASCII characters. So, a scanner with high speed and color quality is desirable. The quality of the scanned document depends up on the scanner. In the document scanning step, a scanner is used to scan the handwritten or printed documents. OCR has three processing steps, Document scanning process, Recognition process and Verifying process. The document image itself can be either machine printed or handwritten, or the combination of two. Optical Character Recognition is a process by which we convert printed document or scanned page to ASCII character that a computer can recognize. Optical Character Recognition extracts the relevant information and automatically enters it into electronic database instead of the conventional way of manually retyping the text. Optical Character Recognition or OCR has enabled scanned documents to become more than just image files, turning into fully searchable documents with text content recognized by computers.
Highlight in 1950s, applied throughout the spectrum of industries resulting into revolutionizing the document management process.
Keywords- OCR, segmentation, neural network, character recognition, hidden markov. In this paper, Several techniques like OCR using correlation method and OCR using neural networks has been discussed. The computer actually recognizes the characters in the document through a transforming technique called Optical Character Recognition. This paper describes the techniques for converting textual content from a paper document into machine readable form. Handwriting recognition has been one of the most interesting and challenging research areas in field of image processing and pattern recognition in the recent years. OCR has been widely used in banking, legal, health care, finance etc. Karishma Tyagi, Vedant Rastogi Department of Computer Science & Engineering, IETĪbstract- Optical Character Recognition has number of applications in day-to-day life. Survey on Character Recognition using OCR Techniques
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