NDLI: A novel algorithm for segmentation and classification of Malayalam characters through characterization using dominant singular values

Content Provider	IEEE Xplore Digital Library
Author	Philip, B. Sudhaker Samuel, R.D.
Copyright Year	2008
Description	Author affiliation: Dept. of Electron. & Commun., S.J. Coll. of Eng., Mysore (Philip, B.; Sudhaker Samuel, R.D.)
Abstract	The rapid process of automation in recent times involves the development of efficient algorithms in machine intelligence. Man-machine interface in most areas of application involves vision systems to recognize texts and objects. In either case this finally reduces to the machine analysis of images ultimately leading to classification of images either as a whole or in segmented form. Images are represented as matrices in some form or the other. Characterization of matrices for efficient classification is a challenging task. Reduction of dimensionality is important in applications that need to handle large number of such matrices. Image recognition and in particular character recognition is an excellent example where large number of image matrices need to be stored and retrieved often at high speed, at the same time performing computational tasks, resulting in requirements of huge memory and computation time. Characterization in various forms could result in reduction in dimensionality to different extents. This paper proposes the use of dominant singular values as distinct characteristic features of rectangular image matrices suitable for reliable classification. Several analysis and outcomes are reported in this paper. A recognition rate of 97.61% has been achieved for the recognition of printed Malayalam characters.
Starting Page	1
Ending Page	6
File Size	2657650
Page Count	6
File Format	PDF
ISBN	9781424435944
DOI	10.1109/ICCCNET.2008.4787718
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-12-18
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Dimensionality reduction Automation Image recognition Intra-subclass distances Segmentation Nearest neighbour classifier Character recognition Machine intelligence Characterization Image segmentation Image analysis Text recognition High performance computing Machine vision Dominant Singular Values User interfaces Optical character recognition (OCR)
Content Type	Text
Resource Type	Article

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