Title :
A note on shape matching using a constructive relaxation method
Author :
Kameyama, Keisuke ; Toraichi, Kazuo ; Kosugi, Yukio
Author_Institution :
Inst. of Inf. Sci. & Electron., Univ. of Tsukuba, Japan
Abstract :
This paper discusses a novel approach for image shape matching to a set of premodelled templates, named as constructive relaxation matching (CRM). In CRM, the modeling stage for a novel input image, conventionally done in the same procedure used for the template modeling, is included in the procedure of iterative relaxation. Upon dynamically constructing the model during relaxation, objects having similar template label assignment probabilities are unified to make one object. The unification of objects develops from model switching maneuvers that have proved to be an efficient method of model selection and parameter determination in training layered neural networks
Keywords :
image classification; image matching; iterative methods; learning (artificial intelligence); neural nets; probability; constructive relaxation method; dynamic model construction; image classification; image matching; iterative relaxation; layered neural network training; model selection; model switching maneuvers; object unification; parameter determination; premodelled templates; shape matching; template label assignment probabilities; Character recognition; Hopfield neural networks; Image analysis; Information science; Labeling; Layout; Neural networks; Noise robustness; Relaxation methods; Shape;
Conference_Titel :
Communications, Computers and signal Processing, 2001. PACRIM. 2001 IEEE Pacific Rim Conference on
Conference_Location :
Victoria, BC
Print_ISBN :
0-7803-7080-5
DOI :
10.1109/PACRIM.2001.953574
