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A novel hybrid approach for salient object detection using local and global saliency in frequency domain

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Abstract

In this paper, we introduce a fast and novel biologically plausible frequency domain approach to detect salient object which incorporates both local and global salient features. The proposed approach involves three phases. In the first phase, locally salient features are obtained as suggested in the research work of Bian and Zhang. Globally salient features are computed in the second phase using fast Walsh-Hadamard transform since it is computationally more efficient and faster than fast Fourier transform. Finally the saliency map is generated in terms of linear weighted combination of local and global saliency maps where the weights are determined using entropy measure. The performance is evaluated both qualitatively and quantitatively on two publicly available datasets and one new dataset derived from a publicly available dataset. Experiments show that the proposed model significantly outperforms other relevant existing state-of-the-art methods in both spatial and frequency domain. The proposed method is also computationally less expensive to detect salient object accurately.

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Notes

  1. http://www.research.microsoft.com/enus/um/people/jiansun/salientobject/salient_object.htm

  2. http://ivrgwww.epfl.ch/supplementary_material/RK_CVPR09/GroundTruth/binarymasks.zip

  3. E-mail at “rinki.arya89 @ gmail.com or navjot.singh.09@gmail.com”

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Acknowledgments

The first author expresses her gratitude to the University Grant Commission (UGC), India for the obtained financial support in performing this research work.

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Authors and Affiliations

  1. School of Computer and Systems Sciences, Jawaharlal Nehru University, New Delhi, 110067, India

    Rinki Arya, Navjot Singh & R. K. Agrawal

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  1. Rinki Arya
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  2. Navjot Singh
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  3. R. K. Agrawal
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Correspondence to Rinki Arya.

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Arya, R., Singh, N. & Agrawal, R.K. A novel hybrid approach for salient object detection using local and global saliency in frequency domain. Multimed Tools Appl 75, 8267–8287 (2016). https://doi.org/10.1007/s11042-015-2750-y

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  • DOI: https://doi.org/10.1007/s11042-015-2750-y

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