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A low computational complexity algorithm for real-time salient object detection

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Abstract

Image saliency detection is a process for highlighting the most salient object in an image and presenting the image saliency map. The content of an image is chaotic, including a complex background, low contrast, and an irregular salient object appearance. To overcome these problems, many algorithms have high computational complexity. In this paper, an efficient and fast-performing saliency detection algorithm is proposed, which consists of initiation saliency map generation and saliency map refinement. In the generation stage, the color-based contrast prior and color-based spatial distribution prior are effectively described in the image. Subsequently, two prior results (contrast value and distribution value) are fused to obtain an initial saliency map. In the refinement stage, the initial saliency map is refined by visual focus and an adaptive salient object mask (SOM). Due to the simplicity of the proposed algorithm, the system can detect salient objects in real time. Experimental evaluation on the benchmark shows that the proposed method can achieve sufficient accuracy and reliability while showing the lowest execution time. Compared with other methods, the execution time of the proposed method can achieve 137 frames per second (FPS) for the dataset with average image size 386 ×  292.

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Authors and Affiliations

  1. Department of Electrical Engineering, National Formosa University, Yunlin, Taiwan

    Wen-Kai Tsai & Ting-Hao Hsu

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  1. Wen-Kai Tsai
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Contributions

All authors contributed to the study’s conception and design. Material preparation, data collection and analysis were performed by Wen-Kai Tsai and Ting-Hao Hsu. The first draft of the manuscript was written by Wen-Kai Tsai and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.

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Correspondence to Wen-Kai Tsai.

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The authors have no relevant financial or nonfinancial interests to disclose. The authors have no conflicts of interest to declare that are relevant to the content of this article. All authors certify that they have no affiliations with or involvement in any organization or entity with any financial interest or nonfinancial interest in the subject matter or materials discussed in this manuscript. The authors have no financial or proprietary interests in any material discussed in this article.

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Tsai, WK., Hsu, TH. A low computational complexity algorithm for real-time salient object detection. Vis Comput 39, 3059–3072 (2023). https://doi.org/10.1007/s00371-022-02513-2

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