| Project/Area Number |
17300044
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| Research Category |
Grant-in-Aid for Scientific Research (B)
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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 | Yokohama National University |
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Principal Investigator |
NAGAO Tomoharu Yokohama National University, Faculty of Environment and Information Sciences, Professor, 大学院環境情報研究院, 教授 (10180457)
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| Project Period (FY) |
2005 – 2006
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| Project Status |
Completed (Fiscal Year 2006)
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| Budget Amount *help |
¥7,100,000 (Direct Cost: ¥7,100,000)
Fiscal Year 2006: ¥2,900,000 (Direct Cost: ¥2,900,000)
Fiscal Year 2005: ¥4,200,000 (Direct Cost: ¥4,200,000)
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| Keywords | Evolutionary Computation / Optimization / Image Processing / Evolutionary Image Processing / GMA / GIN / 動画像処理 / 動画像認識 |
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| Research Abstract |
We studied to develop new evolutionary computation algorithms for complex structures including tree structures with several numerical parameters, network structures, graph structures and so on. Conventional evolutionary algorithms such as GA (Genetic Algorithm) and GP (Genetic Programming) cannot optimize such complex structures.
We developed three kinds algorithms for them.
First, we developed an algorithm named "GMA (Genetic Matrix Algorithm)" for optimization of tree structures with several numerical parameters and applied it to automatic construction of image processing methods.
Second, we constructed GIN (Genetic Image Network) for optimization of network structures whose node is an image filter, and we showed that GIN can generate automatically complex image processing procedures.
Third, we developed GRAPE (GRAph structured Program Evolution) for automatic programming. GRAPE can generate general programs based on machine learning of learning data. For instance, GRAPE can make sorting programs from examples of several original data and their correctly sorted data.
We applied the above methods to automatic generation of image processing algorithms especially motion picture processing such as extraction of human and automobile regions form motion pictures. We can generate complex image processing algorithms very easily using the developed evolutionary algorithms. These methods can be applied to various kinds of fields.
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