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

Volume

1

fYear

2001

fDate

2001

Firstpage

267

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;

fLanguage

English

Publisher

ieee

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

Type

conf

DOI

10.1109/PACRIM.2001.953574

Filename

953574