1995 Fiscal Year Final Research Report Summary

A Study for Inductive Learning of Structural or Topological Features of Images by Genetic Algorithm

Research Project

Project/Area Number	06808034
Research Category	Grant-in-Aid for General Scientific Research (C)
Allocation Type	Single-year Grants
Research Field	Intelligent informatics
Research Institution	Tokyo University of Agriculture and Technology
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)
Project Period (FY)	1994 – 1995
Keywords	genetic algorithm / pictorial feature / inductive learning
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.

(4 results)