IEICE TRANSACTIONS on Information
Object Recognition Using Model Relation Based on Fuzzy Logic
Summary :
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.
- Publication
- IEICE TRANSACTIONS on Information Vol.E79-D No.3 pp.222-229
- Publication Date
- 1996/03/25
- Publicized
- Online ISSN
- DOI
- Type of Manuscript
- PAPER
- Category
- Image Processing,Computer Graphics and Pattern Recognition
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Masanobu IKEDA, Masao IZUMI, Kunio FUKUNAGA, "Object Recognition Using Model Relation Based on Fuzzy Logic" in IEICE TRANSACTIONS on Information,
vol. E79-D, no. 3, pp. 222-229, March 1996, doi: .
Abstract: 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.
URL: https://global.ieice.org/en_transactions/information/10.1587/e79-d_3_222/_p
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@ARTICLE{e79-d_3_222,
author={Masanobu IKEDA, Masao IZUMI, Kunio FUKUNAGA, },
journal={IEICE TRANSACTIONS on Information},
title={Object Recognition Using Model Relation Based on Fuzzy Logic},
year={1996},
volume={E79-D},
number={3},
pages={222-229},
abstract={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.},
keywords={},
doi={},
ISSN={},
month={March},}
Copy
TY - JOUR
TI - Object Recognition Using Model Relation Based on Fuzzy Logic
T2 - IEICE TRANSACTIONS on Information
SP - 222
EP - 229
AU - Masanobu IKEDA
AU - Masao IZUMI
AU - Kunio FUKUNAGA
PY - 1996
DO -
JO - IEICE TRANSACTIONS on Information
SN -
VL - E79-D
IS - 3
JA - IEICE TRANSACTIONS on Information
Y1 - March 1996
AB - 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.
ER -
English
