A robust matching method for low-textured image based on co-occurrence probability of geometry-optimized pixel patterns

Shuichi Akizuki, Manabu Hashimoto

Research output: Contribution to journalArticle

Abstract

In this paper, we propose a template matching algorithm which is applicable for low-textured image like a range image. As for high-speed template matching, the Co-occurrence Probability-based Template Matching (CPTM) is a useful and effective method. This method uses some sets of selected pixel patterns that have relatively low occurrence probability in a template image. By using such a small number of distinctive data, reliable matching has been achieved in addition to high-speed processing. However, this method has a problem that extraction of distinctive pixels will be difficult when distribution of occurrence probability is uniform, for example, it is frequently appeared in range image. We improve the CPTM method for dealing with this problem. A key idea is to optimize geometric pixel relation in the pixel pattern when the proposed method calculates occurrence probability of pixel patterns. Experimental results have confirmed that the proposed method increase the detection rate from 73% to 90% without sacrificing its ability of high-speed. It means that performance of our method is prior to other conventional methods.

Original languageEnglish
JournalIEEJ Transactions on Electronics, Information and Systems
Volume133
Issue number10
DOIs
Publication statusPublished - 2013
Externally publishedYes

Fingerprint

Template matching
Pixels
Geometry
Processing

Keywords

  • Co-occurrence probability
  • Combinatorial optimization
  • Image matching
  • Low-textured image
  • Pixel selection

ASJC Scopus subject areas

  • Electrical and Electronic Engineering

Cite this

A robust matching method for low-textured image based on co-occurrence probability of geometry-optimized pixel patterns. / Akizuki, Shuichi; Hashimoto, Manabu.

In: IEEJ Transactions on Electronics, Information and Systems, Vol. 133, No. 10, 2013.

Research output: Contribution to journalArticle

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