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Optimization algorithm on salient detection

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Abstract

Current studies on salient detection have combined salient cues, such as contrast, prior information, and object edges, which work by segmenting the foreground from the background. However, existing models mostly lose tiny salient regions in scenes and fail to detect all salient regions. In this paper, we propose an optimization algorithm on salient detection based on line sketch. First, we generate the line sketches of images, which include all edges of the salient objects. Second, the detected line sketches are blended into the original images in soft light mode. Then, the sketch works as a mask to highlight the outlines. Finally, the processed images are used in the existing salient detection models. Our contribution is that the salient detection with the sketches extracting image outline can effectively improve the accuracy. Results prove that the proposed algorithm is efficient and improves the performance of models.

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Acknowledgments

This work is supported by the NEPU Natural Science Foundation under Grant No. 2017PY ZL − 05, JY CX_CX06_2018 and JY CX_JG06_2018.

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Authors and Affiliations

  1. School of Electrical and Information Engineering, Northeast Petroleum University, Daqing, 163000, China

    Ning Li & Hongbo Bi

  2. School of Public Administration, School of Fujian Normal University, Fuzhou, 350117, China

    Huaping Guan

  3. XJ ELECTRIC CO., LTD, Xuchang, 461000, China

    Yulong Li

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  1. Ning Li
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  2. Hongbo Bi
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  3. Huaping Guan
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  4. Yulong Li
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Correspondence to Hongbo Bi.

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Li, N., Bi, H., Guan, H. et al. Optimization algorithm on salient detection. Multimed Tools Appl 79, 6437–6445 (2020). https://doi.org/10.1007/s11042-019-08381-8

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