Hand Printed Character Recognition Using Neural Networks

In this paper an attempt is made to recognize hand-printed characters by using features extracted using the proposed sector approach. In this approach, the normalized and thinned character image is divided into sectors with each sector covering a fixed angle. The features totaling 32 include vector distances, angles, occupancy and end-points. For recognition, both neural networks and fuzzy logic techniques are adopted. The proposed approach is implemented and tested on hand-printed isolated character database consisting of English characters, digits and some of the keyboard special characters

Use of colour for hand-filled form analysis and recognition

Colour information in form analysis is currently under utilised. As technology has advanced and computing costs have reduced, the processing of forms in colour has now become practicable. This paper describes a novel colour-based approach to the extraction of filled data from colour form images. Images are first quantised to reduce the colour complexity and data is extracted by examining the colour characteristics of the images. The improved performance of the proposed method has been verified by comparing the processing time, recognition rate, extraction precision and recall rate to that of an equivalent black and white system

RECOGNITION OF PRINTED KANNADA NUMERALS BY NEAREST NEIGHBOR METHOD

Numeral recognition is considered to be very prominent in most of the Character recognition researches. With respect to applications like number plate recognition and document processing the numerals are composed as a part of number plate images/application form type document images. This paper mainly focuses on eliminating language barriers that may arise while comprehending the regional language numerals by a non-regional user at the time of number plate recognition or other application form type document processing with special reference to Karnataka state. An algorithm is devised by incorporating the capabilities of functionalities of features the handwritten and printed Kannada numerals

Form Design for High Accuracy Optical Character Recognition

Financial institutions, insurance companies, and government agencies are all aggressively pursuing the integration of automated forms processing into their everyday work flows. To use existing optical character recognition (OCR) technology, the forms that are currently hand-keyed will probably need to be redesigned. This paper presents some of the quantitative results generated by a comprehensive study of three versions of a redesigned tax form. Analyses show that using separately spaced bounding character boxes to represent fields provides superior machine readability over fields without character boxes, fields containing vertical ticks (combs), and fields with adjoining character boxes. It is also shown that character boxes containing two vertically stacked ovals cause writers much more difficulty to complete than do empty character boxes. The analyses also provide quantitative proof that writer idiosyncratic responses on forms are the major source of errors within the recognition sy..