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Striped-texture image segmentation with application to multimedia security

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Abstract

In today’s rapid growth of volume of multimedia data, security is important yet challenging problem in multimedia applications. Image, which covers the highest percentage of the multimedia data, it is very important for multimedia security. Image segmentation is utilized as a fundamental preprocessing of various multimedia applications such as surveillance for security by breaking a given image into multiple salient regions. In this paper, we present a new image segmentation approach based on frequency-domain filtering for images with stripe texture, and generalize it to lattice fence images. Our method significantly reduces the impact of stripes on segmentation performance. The approach proposed in this paper consists of three phases. Given the images, we weaken the effect of stripe texture by filtering in the frequency domain automatically. Then, structure-preserving image smoothing is employed to remove texture details and extract the main image structures. Last, we use an effective threshold method to produce segmentation results. Our method achieves very promising results for the test image dataset and could benefit a number of new multimedia applications such as public security.

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Acknowledgments

This work was supported by the National Natural Science Foundation of China (grant number 61472348).

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Authors and Affiliations

  1. College of Computer Science and Technology, Zhejiang University, CaoGuangBiao Building, 38 Zheda Road, Hangzhou, 310027, People’s Republic of China

    Jinxiong Ren & Gang Chen

  2. Hangzhou Research Institute, Netease(hangzhou), Inc., 599 Wangshang Road, Hangzhou, 310052, People’s Republic of China

    Xiaoyan Li & Kuang Mao

Authors
  1. Jinxiong Ren
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  2. Gang Chen
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  3. Xiaoyan Li
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  4. Kuang Mao
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Correspondence to Jinxiong Ren.

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Ren, J., Chen, G., Li, X. et al. Striped-texture image segmentation with application to multimedia security. Multimed Tools Appl 78, 26965–26978 (2019). https://doi.org/10.1007/s11042-017-4479-2

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  • DOI: https://doi.org/10.1007/s11042-017-4479-2

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