Title :
Heeding more than the top template
Author :
Sarkar, Prateek ; Nagy, George
Author_Institution :
Dept. of Electr. Comput. & Syst. Eng., Rensselaer Polytech. Inst., Troy, NY, USA
Abstract :
We present a method of classifying a pattern using information furnished by a ranked list of templates, rather than just the best matching template. We propose a parsimonious model to compute the class-conditional likelihood of a list of templates ranked on the basis of their match scores. We discuss the estimation of parameters used in the model. The results of maximum likelihood classification on isolated digit patterns consistently show a 10-20% relative gain in recognition accuracy when we use more than one top-template
Keywords :
character recognition; maximum likelihood estimation; pattern classification; pattern matching; best matching template; class-conditional likelihood; isolated digit patterns; match scores; maximum likelihood classification; parameter estimation; pattern classification; ranked template list; recognition accuracy; Buildings; Character recognition; Maximum likelihood estimation; Optical character recognition software; Parameter estimation; Pattern recognition; Radio access networks; Shape; Systems engineering and theory; Testing;
Conference_Titel :
Document Analysis and Recognition, 1999. ICDAR '99. Proceedings of the Fifth International Conference on
Conference_Location :
Bangalore
Print_ISBN :
0-7695-0318-7
DOI :
10.1109/ICDAR.1999.791804
