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Proceedings Paper

Genetic algorithm based image binarization approach and its quantitative evaluation via pooling
Author(s): Huijun Hu; Ya Liu; Maofu Liu
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Paper Abstract

The binarized image is very critical to image visual feature extraction, especially shape feature, and the image binarization approaches have been attracted more attentions in the past decades. In this paper, the genetic algorithm is applied to optimizing the binarization threshold of the strip steel defect image. In order to evaluate our genetic algorithm based image binarization approach in terms of quantity, we propose the novel pooling based evaluation metric, motivated by information retrieval community, to avoid the lack of ground-truth binary image. Experimental results show that our genetic algorithm based binarization approach is effective and efficiency in the strip steel defect images and our quantitative evaluation metric on image binarization via pooling is also feasible and practical.

Paper Details

Date Published: 17 December 2015
PDF: 7 pages
Proc. SPIE 9811, MIPPR 2015: Multispectral Image Acquisition, Processing, and Analysis, 98110P (17 December 2015); doi: 10.1117/12.2204902
Show Author Affiliations
Huijun Hu, Wuhan Univ. (China)
Wuhan Univ. of Science and Technology (China)
Ya Liu, Wuhan Univ. of Science and Technology (China)
Maofu Liu, Wuhan Univ. of Science and Technology (China)


Published in SPIE Proceedings Vol. 9811:
MIPPR 2015: Multispectral Image Acquisition, Processing, and Analysis
Jinxue Wang; Zhiguo Cao; Jayaram K. Udupa; Henri Maître, Editor(s)

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