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An automatic region detection and processing approach in genetic programming for binary image classification

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posted on 2021-02-11, 02:26 authored by Ying Bi, Mengjie ZhangMengjie Zhang, Bing XueBing Xue
© 2017 IEEE. In image classification, region detection is an effective approach to reducing the dimensionality of the image data but requires human intervention. Genetic Programming (GP) as an evolutionary computation technique can automatically identify important regions, and conduct feature extraction, feature construction and classification simultaneously. In this paper, an automatic region detection and processing approach in GP (GP-RDP) method is proposed for image classification. This approach is able to evolve important image operators to deal with detected regions for facilitating feature extraction and construction. To evaluate the performance of the proposed method, five recent GP methods and seven non-GP methods based on three types of image features are used for comparison on four image data sets. The results reveal that the proposed method can achieve comparable performance on easy data sets and significantly better performance on difficult data sets than the other comparable methods. To further demonstrate the interpretability and understandability of the proposed method, two evolved programs are analysed. The analysis shows the good interpretability of the GP-RDP method and proves that the GP-RDP method is able to identify prominent regions, evolve effective image operators to process these regions, extract and construct good features for efficient image classification.

History

Preferred citation

Bi, Y., Zhang, M. & Xue, B. (2018, July). An automatic region detection and processing approach in genetic programming for binary image classification. In International Conference Image and Vision Computing New Zealand 2017 International Conference on Image and Vision Computing New Zealand (IVCNZ), Christchurch, NEW ZEALAND (2017-December pp. 1-6). IEEE. https://doi.org/10.1109/IVCNZ.2017.8402469

Conference name

2017 International Conference on Image and Vision Computing New Zealand (IVCNZ)

Conference Place

Christchurch, NEW ZEALAND

Conference start date

2017-12-04

Conference finish date

2017-12-06

Title of proceedings

International Conference Image and Vision Computing New Zealand

Volume

2017-December

Series

International Conference on Image and Vision Computing New Zealand

Publication or Presentation Year

2018-07-03

Pagination

1-6

Publisher

IEEE

Publication status

Published

ISSN

2151-2191

eISSN

2151-2205