Paper Info
Title
Handwritten Digit Recognition By Hierarchical Displacement Extraction With Gradual Prototype Elimination
Abstract
This paper investigates the performance of a handwritten character recognition method by hierarchical displacement extraction based on. NIST special database (HSF7). The method is composed of a displacement extraction technique and a coarse-to-fine search strategy. In the displacement extraction technique, the displacement (correspondent between an input pattern. and a prototype is iteratively computed by minimizing a functional defined in the framework of regularization theory. In the coarse-to-fine search strategy, the above-mentioned displacement is determined with multi-resolution images so as to avoid the pitfalls of local minimum and make the number of iterations low. In addition, a new idea is proposed for reducing the cost of computation without degrading the recognition performance, in which the number of candidate prototypes is eliminated gradually through the hierarchical procedure of the coarse-to-fine search strategy.
Year
DOI
Venue
2000
10.1109/ICPR.2000.906082
15TH INTERNATIONAL CONFERENCE ON PATTERN RECOGNITION, VOL 2, PROCEEDINGS: PATTERN RECOGNITION AND NEURAL NETWORKS
Keywords
Field
DocType
nist,degradation,prototypes,databases,minimization,data engineering,handwriting recognition,minimisation,iterative methods
Computer vision,Character recognition,Pattern recognition,Iterative method,Computer science,NIST,Minimisation (psychology),Artificial intelligence,Digit recognition,Regularization theory,Computation
Conference
ISSN
Citations 
PageRank 
1051-4651
2
0.59
References 
Authors
5
3
Name
Order
Citations
PageRank
Yoshiki Mizukami1648.94
Taiji Sato241.24
Kanya Tanaka31812.75