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A Gradient Weighted Thresholding Method for Image Segmentation

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Intelligence Science and Big Data Engineering. Image and Video Data Engineering (IScIDE 2015)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 9242))

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Abstract

Otsu method is widely used for image thresholding, which only considers the gray level information of the pixels. Otsu method can provide satisfactory result for thresholding an image with a histogram of clear bimodal distribution. This method, however, fails if the variance or the class probability of the object is much smaller than that of the background. In order to introduce more information of the image, a gradient weighted threholding method is presented, which weighs the objective function of the Otsu method with the gray level and gradient mapping (GGM) function. It makes the between-class variance of the thresholded image maximize and the threshold locate as close to the boundary of the object and the background as possible. The experimental results on optical images as well as infrared images show the effectiveness of the proposed method.

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Acknowledgements

This work is supported by National Science Foundation of China (Grant No. 61102095,61202183,61340040). And thanks for Dr. Liu Ying on the help of the language.

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Authors and Affiliations

  1. School of Communication and Information Engineering, Xi’an University of Posts and Telecommunications, Xi’an, 710121, People’s Republic of China

    Bo Lei & Jiu-lun Fan

Authors
  1. Bo Lei
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  2. Jiu-lun Fan
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Corresponding author

Correspondence to Bo Lei .

Editor information

Editors and Affiliations

  1. Zhejiang University, Hangzhou, China

    Xiaofei He

  2. Xidian University, Xi'an, China

    Xinbo Gao

  3. Northwestern Polytechnical University, Shaanxi, China

    Yanning Zhang

  4. Nanjing University, Nanjing, China

    Zhi-Hua Zhou

  5. Chinese Academy of Sciences, Beijing, China

    Zhi-Yong Liu

  6. Suzhou University of Science and Technology, Suzhou, China

    Baochuan Fu

  7. Suzhou University of Science and Technology, Jiangsu, China

    Fuyuan Hu

  8. Suzhou University of Science and Technology, Jiangsu, China

    Zhancheng Zhang

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© 2015 Springer International Publishing Switzerland

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Lei, B., Fan, Jl. (2015). A Gradient Weighted Thresholding Method for Image Segmentation. In: He, X., et al. Intelligence Science and Big Data Engineering. Image and Video Data Engineering. IScIDE 2015. Lecture Notes in Computer Science(), vol 9242. Springer, Cham. https://doi.org/10.1007/978-3-319-23989-7_31

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  • DOI: https://doi.org/10.1007/978-3-319-23989-7_31

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-23987-3

  • Online ISBN: 978-3-319-23989-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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