| Project/Area Number |
11680407
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Research Field |
Intelligent informatics
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| Research Institution | Fukuyama University |
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Principal Investigator |
MORI Katsumi FUKUYAMA UNIVERSITY, DEPARTMENT OF ENGINEERING, PROFESSOR, 工学部, 教授 (60200359)
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| Co-Investigator(Kenkyū-buntansha) |
WATANABE Eiji KONAN UNIVERSITY, DEPARTMENT OF SCIENCE AND ENGINEERING, ASSOCIATE PROFESSOR, 理工学部, 助教授 (20220866)
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| Project Period (FY) |
1999 – 2001
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| Project Status |
Completed (Fiscal Year 2001)
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| Budget Amount *help |
¥3,400,000 (Direct Cost: ¥3,400,000)
Fiscal Year 2001: ¥800,000 (Direct Cost: ¥800,000)
Fiscal Year 2000: ¥900,000 (Direct Cost: ¥900,000)
Fiscal Year 1999: ¥1,700,000 (Direct Cost: ¥1,700,000)
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| Keywords | object recognition / lighting recognition / cooperative processing / elliptic contour / multi-layered neural nerwork / predicted scene CG image / color compensation / region segmentation / 光環境認識 / シーン予測 / 画像の圧縮 / CG画像 / 回転軸対称物体 / 楕円弧 |
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| Research Abstract |
For the purpose of development of the assistant robot for handicapped and aged persons, we have developed some recognition methods for objects in artificial and natural lightings.
[1] Recognition of environmental lighting :
(1) Color compensation : We have developed a method for the detection of the changing property of the environmental lighting by using neural networks, and shown that this method could be applied to the compensation of real scene images changed by artificial and natural lightings.
(2) Segmentation and compression for real scene images : By using multiple neural networks with the cooperative function, we have developed segmentation and compression methods for real scene images changed by artificial and natural lightings. Also we have shown that their methods could detect the changing property of the environmental lighting.
[2] Object recognition based on the shape analysis :
(1) Recognition of circular objects : We have made some algebraic formulas for representing the geometrical properties of ellipses that they have diameters and conjugate diameters, and shown that circular objects could be recognized accurately in short processing time by using the formulas.
(2) Contour segmentation : Because most of contours obtained from real images become links of edges of different objects, we have proposed a method to segment the contours into individual object sections by estimating the curvatures of neighboring contours.
[3] Cooperative recognition of environments and objects : We have proposed a scene predicting CG-system for supporting the cooperative recognition of environmental lighting and objects, and shown experimentally that the system is very effective to recognize objects and environmental lightings in real scene. The system drastically cuts the processing cost of recognizing objects in closed space influenced by time-variant lighting.
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