Local stereovision matching through the ADALINE neural network

被引：12
|
作者：
Pajares, G [1 ]
de la Cruz, JM [1 ]
机构：
[1] Univ Complutense Madrid, Fac Ciencias Fis, Dept Arquitectura Computadores & Atomat, E-28040 Madrid, Spain
来源：
PATTERN RECOGNITION LETTERS | 2001年 / 22卷 / 14期
关键词：
neural networks; ADALINE; delta rule; training; learning; stereovision; matching; similarity;
D O I：
10.1016/S0167-8655(01)00097-6
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
This paper presents an approach to the local stereovision matching problem using edge segments as features with four attributes. Based on these attributes we compute a matching probability between pairs of features of the stereo images. A correspondence is said to be true when this probability is maximum. The probability value is a weighted sum of the attributes. We use two combined ADALINE neural networks to compute the weight for each attribute. A comparative analysis among other recent matching methods is illustrated. (C) 2001 Elsevier Science B.V. All rights reserved.
引用
收藏
页码：1457 / 1473
页数：17
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