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CoBRa: convex hull based random walks for salient object detection

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Abstract

Salient object detection is a challenging research area, which aims to highlight significant region of the visual scene more accurately and quickly. In this research direction, we propose a novel saliency detection model called Convex Hull Based Random Walks (CoBRa) approach. In the proposed model, an image is segmented into superpixels and Convex Hull is constructed based on the segmented image to roughly partition the segmented image into two regions: CH-foreground and CH-background regions and the centroid of the CH-foreground region is calculated. Then, initial saliency is computed by using two priors viz. contrast and center priors. Here, the proposed model exploits CH-foreground region centroid obtained by Convex Hull to computed center prior which is more efficient than image center. Afterwards, two thresholds are empirically obtained and applied on initial saliency map to produce two binary segmented images. Based on these two binary images, the proposed model collects foreground and background seeds. These seeds are further refined with CH-foreground and CH-background regions to produce reliable and effective seeds. Finally, a random walk is constructed with the determined seeds to generate a pixel-wise saliency map. The superiority of the proposed model is validated via extensive experimental results performed on six publicly available datasets viz. MSRA10K, DUT-OMRON, ECSSD, PASCAL-S, SED2, and THUR15K. The performance of the proposed model was compared with eight state-of-the-art methods in terms of Precision, Recall, F-Measure, Receiver Operating Characteristics (ROC), and Area under the curve (AUC). The proposed method outperforms or comparable with compared methods in terms of all the performance measures.

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Acknowledgements

We acknowledge Ministry of Human Resource Development Government of India, India for supporting this research by providing fellowship to one of the author Mr. Vivek Kumar Singh.

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  1. Department of Computer Science and Engineering, National Institute of Technology, Uttarakhand, India

    Vivek Kumar Singh & Nitin Kumar

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  1. Vivek Kumar Singh
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Correspondence to Vivek Kumar Singh.

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Singh, V.K., Kumar, N. CoBRa: convex hull based random walks for salient object detection. Multimed Tools Appl 81, 30283–30303 (2022). https://doi.org/10.1007/s11042-022-12470-6

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  • DOI: https://doi.org/10.1007/s11042-022-12470-6

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