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A New Balanced Greedy Snake Algorithm

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The 8th International Conference on Computer Engineering and Networks (CENet2018) (CENet2018 2018)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 905))

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Abstract

The existing greedy snake algorithm (GSA) suffers from some problems, such as three forces are unbalance and the extracting contour on concave region is unsatisfactory. This paper presents an algorithm, called balanced greedy snake algorithm (BGSA), for solving objective contour extraction problem. BGSA is compose of continuity force, curvature force and image force, which is similar to the origin GSA. Whereas, BGSA improved the computing rule of GSA to balance the influence of above three forces. Especially, BGSA can process the image with concave region well. The results of experiment show that BGSA is efficient and outperform the existing GSA.

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References

  1. Lie, W.N.: Automatic target segmentation by locally adaptive image thresholding. IEEE Trans. Image Process. 4(7), 1036–1041 (1995)

    Article  Google Scholar 

  2. McInernery, T., Terzopolous, D.: Deformable models in medical image analysis: a survey. Med. Image Anal. 1(2), 91–108 (1996)

    Article  Google Scholar 

  3. Jain, A.K., Smith, S.P., Backer, E.: Segmentation of muscle cell pictures: a preliminary study. IEEE Trans. Pattern Anal. Mach. Intell. 2(3), 232–242 (1980)

    Article  Google Scholar 

  4. Fok, Y.L., Chan, J.C.K., Chin, R.T.: Automated analysis of nerve cell images using active contour models. IEEE Trans. Med. Image 15(3), 353–368 (1996)

    Article  Google Scholar 

  5. Ginneken, B., Frangi, A.F., Staal, J.J.: Active shape model segmentation with optimal features. IEEE Trans. Med. Image 21(8), 924–933 (2002)

    Article  Google Scholar 

  6. Kass, M., Witkin, A., Terzopoulos, D.: Snakes: active contour models. Int. J. Comput. Vis. 1(4), 321–331 (1987)

    Article  Google Scholar 

  7. Williams, D.J., Shah, M.: A fast algorithm for active contours and curvature estimation. Comput. Vis. Graph. Image Process. 55, 14–26 (1992)

    MATH  Google Scholar 

  8. Lam, K.M., Yan, H.: Fast algorithm for locating head boundaries. J. Electron. Image 3(4), 352–359 (1994)

    Google Scholar 

  9. Mustafa, S., Lam, K.M., Yan, H.: A faster converging snake algorithm to locate object boundaries. IEEE Trans. Image Process. 15(5), 1182–1191 (2013)

    Google Scholar 

Download references

Acknowledgement

This work is supported by the National Natural Science Foundation of China (Grant No. 71301078), the Natural Science Foundation of Education Bureau of Jiangsu Province (Grant No. 16KJB520049) and the Natural Science Foundation of Huaian City (Grant No. HAB201709).

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Authors and Affiliations

  1. Department of Computer Science and Engineering, Huaian Vocational College of Information Technology, Huaian, 223003, China

    Le Cheng, Liping Zheng, Haibo Wang, Yanhong Song & Jihong Gao

  2. College of Computer and Information, Hohai University, Nanjing, 210098, China

    Le Cheng

Authors
  1. Le Cheng
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  2. Liping Zheng
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  3. Haibo Wang
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  4. Yanhong Song
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  5. Jihong Gao
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Corresponding author

Correspondence to Le Cheng .

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Editors and Affiliations

  1. School of Computing, Edinburgh Napier University, Edinburgh, UK

    Qi Liu

  2. College of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics, Nanjing, China

    Mustafa Mısır

  3. School of Computer, Fudan University, Shanghai, China

    Xin Wang

  4. College of Information Science and Technology/College of Cyber Security, Jinan University, Guangzhou, China

    Weiping Liu

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Cheng, L., Zheng, L., Wang, H., Song, Y., Gao, J. (2020). A New Balanced Greedy Snake Algorithm. In: Liu, Q., Mısır, M., Wang, X., Liu, W. (eds) The 8th International Conference on Computer Engineering and Networks (CENet2018). CENet2018 2018. Advances in Intelligent Systems and Computing, vol 905. Springer, Cham. https://doi.org/10.1007/978-3-030-14680-1_62

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