DocumentCode :
3601045
Title :
A Genetic-Algorithm-Based Explicit Description of Object Contour and its Ability to Facilitate Recognition
Author :
Hui Wei ; Xue-Song Tang
Author_Institution :
Dept. of Comput. Sci., Fudan Univ., Shanghai, China
Volume :
45
Issue :
11
fYear :
2015
Firstpage :
2558
Lastpage :
2571
Abstract :
Shape representation is an extremely important and longstanding problem in the field of pattern recognition. Closed contour, which refers to shape contour, plays a crucial role in the comparison of shapes. Because shape contour is the most stable, distinguishable, and invariable feature of an object, it is useful to incorporate it into the recognition process. This paper proposes a method based on genetic algorithms. The proposed method can be used to identify the most common contour fragments, which can be used to represent the contours of a shape category. The common fragments clarify the particular logics included in the contours. This paper shows that the explicit representation of the shape contour contributes significantly to shape representation and object recognition.
Keywords :
genetic algorithms; image representation; object recognition; shape recognition; genetic-algorithm-based explicit description; object contour; object feature; pattern recognition; shape category; shape representation; Biological cells; Genetic algorithms; Image segmentation; Laboratories; Object recognition; Partitioning algorithms; Shape; Genetic algorithm (GA); object recognition; shape representation;
fLanguage :
English
Journal_Title :
Cybernetics, IEEE Transactions on
Publisher :
ieee
ISSN :
2168-2267
Type :
jour
DOI :
10.1109/TCYB.2014.2376939
Filename :
6998871
Link To Document :
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