SHAPE-RECOGNITION WITH A NEURAL CLASSIFIER BASED ON A FAST POLYGON APPROXIMATION TECHNIQUE

被引：28

作者：

MITZIAS, DA

MERTZIOS, BG

机构：

[1] DEMOCRITUS UNIV THRACE,DEPT ELECTR & COMP ENGN,THRACE,GREECE

[2] DEMOCRITUS UNIV THRACE,DEPT ELECT ENGN,THRACE,GREECE

[3] DEMOCRITUS UNIV THRACE,AUTOMAT CONTROL SYST LAB,THRACE,GREECE

[4] UNIV TORONTO,TORONTO M5S 1A1,ONTARIO,CANADA

来源：

PATTERN RECOGNITION | 1994年 / 27卷 / 05期

关键词：

POLYGON APPROXIMATION; CONTOUR FOLLOWING; DATA REDUCTION OF DIGITIZED CURVE; CLASSIFICATION; NEURAL NETWORKS;

D O I：

10.1016/0031-3203(94)90042-6

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

A method is presented for the fast recognition of two-dimensional (2D) binary shapes with complicated form, like islands on a map or medical images. The proposed method is based on a new polygon approximation technique, which extracts suitable feature vectors with specified dimension, which characterizes a given shape. These feature vectors are used as inputs in an efficient neural based classifier for the fast recognition of the shape. The proposed technique is characterized by high speed performance, which is desired for real time applications.

引用

页码：627 / 636

页数：10

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