A Study for Inductive Learning of Structural or Topological Features of Images by Genetic Algorithm
| Project/Area Number |
06808034
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| Research Category |
Grant-in-Aid for General Scientific Research (C)
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| Allocation Type | Single-year Grants |
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| Research Field |
Intelligent informatics
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| Research Institution | Tokyo University of Agriculture and Technology |
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Principal Investigator |
KANEKO Shun'ichi Tokyo University of Agriculture and Technology, Graduate School of Bio-application and Systems Engineering, Associate Professor, 生物システム応用科学研究科, 助教授 (50134789)
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| Project Period (FY) |
1994 – 1995
|
| Project Status |
Completed (Fiscal Year 1995)
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| Budget Amount *help |
¥1,800,000 (Direct Cost: ¥1,800,000)
Fiscal Year 1995: ¥600,000 (Direct Cost: ¥600,000)
Fiscal Year 1994: ¥1,200,000 (Direct Cost: ¥1,200,000)
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| Keywords | genetic algorithm / pictorial feature / inductive learning / 構造的特徴 / 位相的特徴 / 形状特徴 / パタン認識 |
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| Research Abstract |
The following results have been obtained in the term of the project :
(1) We have designed a segmentation algorithm of closed contours based on genetic algorithm, and then implemented a prototype system.
(2) We have obtained a successful results with some sets of character fonts.
(3) Depending on classification information, we have had successful results in the experimentation of automatic classification.
(4) We have designed a selection algorithm of primitive features of each class, and then had sufficient experimental results.
(5) Using the training feature set abovementioned, we got sufficient results.
(6) We have considered a representation scheme of general primitive shapes.
(7) We have considered fundamentally a possibility of automatic generation of recognizer programs.
(8) We have considered a shape matching algorithm based on the extracted primitive shape features.
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Report
(3 results)
Research Products
(7 results)
