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Robust seed selection of foreground and background priors based on directional blocks for saliency-detection system

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Abstract

Visual perception modelling of saliency detection has received widespread concerns recently from both the cybernetics and computational intelligence domains. In particular, those distinct background and foreground-oriented models are capable of engendering competitive results. The implicitly vital issue of the above computing approaches is how to reliably choose seeds of the foreground and background cues for kicking off the subsequent saliency-detection procedure. To address this barrier, this paper explores the local geometry and statistical attribute of the detected orientational blocks via an improved discrete wavelet frame transform algorithm to estimate the center position of individual salient object in the original input. Specially, the calculated centroid can be regarded as the prominent focus of visual perception in the initial image, which is beneficial to choose the credible seed during the computing of the superpixel-based foreground and background cues. Then, both sides of the complementary and visually oriented cues are integrated concurrently into a dependable and robust saliency map with reliability. Substantial experimental evaluations in term of freely open-access databases testify the effectiveness of the designed framework, and have prove that the designed algorithm is accurate and outperforms the other distinct representative saliency detection algorithms.

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Acknowledgments

This work was supported by National Natural Science Foundation of China (NSFC) (61976123, 61601427, 61876098); the Taishan Young Scholars Program of Shandong Province; Royal Society - K. C. Wong International Fellowship (NIF\R1\180909); and Key Development Program for Basic Research of Shandong Province (ZR2020ZD44).

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Authors and Affiliations

  1. School of Computer Science and Technology, Shandong University of Finance and Economics, Jinan, China

    Muwei Jian

  2. School of Information Science and Engineering, Linyi University, Linyi, China

    Muwei Jian

  3. School of Creative Technologies, University of Portsmouth, Portsmouth, UK

    Muwei Jian & Hui Yu

  4. Department of Computer Science and Technology, Ocean University of China, Qingdao, China

    Ruihong Wang & Junyu Dong

  5. Shandong Institute of Commerce and Technology, Jinan, 250103, China

    Hong Xu

  6. School of Software, Shandong University, Jinan, 250101, China

    Hong Xu & Yilong Yin

  7. Key Laboratory of Metallurgical Equipment and Control Technology, Wuhan University of Science and Technology, Wuhan, China

    Gongfa Li

  8. Department of Electronic and Information Engineering, The Hong Kong Polytechnic University, Kowloon, Hong Kong

    Kin-Man Lam

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  1. Muwei Jian
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  2. Ruihong Wang
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  3. Hong Xu
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Correspondence to Hong Xu or Hui Yu.

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Jian, M., Wang, R., Xu, H. et al. Robust seed selection of foreground and background priors based on directional blocks for saliency-detection system. Multimed Tools Appl 82, 427–451 (2023). https://doi.org/10.1007/s11042-022-13125-2

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  • DOI: https://doi.org/10.1007/s11042-022-13125-2

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