The New Jersey Institute of Technology's
Electronic Theses & Dissertations Project

Title:	Character recognition using string matching
Author:	Ye, Xiaozhi
View Online:	njit-etd1992-120 (ix, 23 pages ~ 0.7 MB pdf)
Department:	Department of Computer and Information Science
Degree:	Master of Science
Program:	Computer and Information Science
Document Type:	Thesis
Advisory Committee:	Wang, David T. (Committee chair)
Date:	1992-10
Keywords:	Optical character recognition devices
Availability:	Unrestricted
Abstract:	To handle noisy and distorted pattern is the use of similarity or distance measures. A similarity or distance measure can be defined between a representation of an unknown pattern and a representation of a prototype pattern. Recognition of the unknown pattern can be carried out on the basis of the maximum-similarity or minimum distance criterion (Bunke 1990) This approach is proposed to recognize the noisy or distorted character image. In this work, a directly string representation of the pattern ( prototype as well as unknown input) using the histogram method, a decision procedure for classification is the well known Levenshtein distance or weighted Levenshtein distance (Wanger 1974; Hall and Dowling 1980), the cost of a transformation is specially estimated, and typical elements of the sample set are chosen and a well known statistical decision--nearest neighbor classification (NN-classification) is applied.(P. A. Devijver and J. Kitler 1982) Experiments show that it is an efficient method and it gives satisfactory results.