Hierarchical object recognition from a 2D image using a genetic algorithm

Yuichi Abe, Masafumi Hagiwara

Research output: Contribution to journalConference article

3 Citations (Scopus)

Abstract

A new approach for object recognition is proposed in this paper. Many methods to recognize objects have been studied. Most of them required one precise object model for recognizing only one object. Accordingly it is necessary to prepare a model for only one object in advance. Moreover it is difficult to make the precise model, and a long computational time is necessary to match it with an input image. In this paper, a hierarchical object recognition method using a genetic algorithm (GA) is proposed. GAs have features to provide robust search in complex spaces. Therefore GAs are suitable for object recognition problems which have many parameters. In the proposed method, at first the input image is simplified, and then the simplified image is matched with a fundamental model. By means of the hierarchical method, a precise object model is not necessary, and only one fundamental model represents the objects which belong to the same category.

Original languageEnglish
Pages (from-to)2549-2554
Number of pages6
JournalProceedings of the IEEE International Conference on Systems, Man and Cybernetics
Volume3
Publication statusPublished - 1997 Dec 1
EventProceedings of the 1997 IEEE International Conference on Systems, Man, and Cybernetics. Part 3 (of 5) - Orlando, FL, USA
Duration: 1997 Oct 121997 Oct 15

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Hardware and Architecture

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