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Object Recognition Using Model Relation Based on Fuzzy Logic
Masanobu IKEDA Masao IZUMI Kunio FUKUNAGA
IEICE TRANSACTIONS on Information and Systems
Publication Date: 1996/03/25
Print ISSN: 0916-8532
Type of Manuscript: PAPER
Category: Image Processing,Computer Graphics and Pattern Recognition
computer vision, object recognition, aspect image, fuzzy relation system, fuzzy integral,
Full Text: PDF(586.7KB)>>
Understanding unknown objects in images is one of the most important fields of the computer vision. We are confronted with the problem of dealing with the ambiguity of the image information about unknown objects in the scene. The purpose of this paper is to propose a new object recognition method based on the fuzzy relation system and the fuzzy integral. In order to deal with the ambiguity of the image information, we apply the fuzzy theory to object recognition subjects. Firstly, we define the degree of similarity based on the fuzzy relation system among input images and object models. In the next, to avoid the uncertainty of relations between the input image and the 2-D aspects of models, we integrate the degree of similarity obtained from several input images by the fuzzy integral. This proposing method makes it possible to recognize the unknown objects correctly under the ambiguity of the image information. And the validity of our method is confirmed by the experiments with six kinds of chairs.