A Study for Inductive Learning of Structural or Topological Features of Images by Genetic Algorithm
Grant-in-Aid for General Scientific Research (C)
|Allocation Type||Single-year Grants|
|Research Institution||Tokyo University of Agriculture and Technology|
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)
|Project Period (FY)
1994 – 1995
Completed(Fiscal Year 1995)
|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)
|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|
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.
Research Output (7results)