文章基本信息

标题：Template Matching using Statistical Model and Parametric Template for Multi-Template
本地全文：下载
作者：Chin-Sheng Chen ; Jian-Jhe Huang ; Chien-Liang Huang 等
期刊名称：Journal of Signal and Information Processing
印刷版ISSN：2159-4465
电子版ISSN：2159-4481
出版年度：2013
卷号：4
期号：3B
页码：52-57
DOI：10.4236/jsip.2013.43B009
出版社：Scientific Research Publishing
摘要：This paper represents a template matching using statistical model and parametric template for multi-template. This algorithm consists of two phases: training and matching phases. In the training phase, the statistical model created by principal component analysis method (PCA) can be used to synthesize multi-template. The advantage of PCA is to reduce the variances of multi-template. In the matching phase, the normalized cross correlation (NCC) is employed to find the candidates in inspection images. The relationship between image block and multi-template is built to use parametric template method. Results show that the proposed method is more efficient than the conventional template matching and parametric template. Furthermore, the proposed method is more robust than conventional template method.
关键词：Multi-Template; Template Matching; Parametric Template; Normalized Cross Correlation; Principal Component Analysis; Statistical Model