Our presentation will focus on adaptive character recognition. We will present a method where features at different resolutions, from coarse to fine-grained, are implemented by means of a recursive classification scheme. We present a method that adaptively determines the degree of resolution necessary in order to classify an input pattern. This leads to optimal use of computational resources. The adaptive character recognizer dynamically adapts to factors such as the quality of the input pattern, its intrinsic similarities and differences from patterns of other classes it is being compared against and the processing time available.
Experimental results support the methodology presented.
Venu Govindaraju received his PhD in computer science from the State University of new York at Buffalo in 1992. He has coauthored more than 80 technical papers in various International journals and conferences and has one US patent. He is the associate editor of the Journal of Pattern Recognition and the area chair of the IEEE SMC technical committee for pattern recognition. Dr. Govindaraju has been a co-principal investigator on several federally sponsored and industry sponsored projects. He is presently leading multiple projects on postal applications.