Abstract
Salient Object Detection (SOD) has several applications including image and video compression, video summarization, image segmentation and object discovery etc. Several Methods have been suggested in literature for detecting salient object in digital images. Most of these methods aim at detecting salient objects in images which does not contain any artifact such as noise. In this paper, we have evaluated several salient object detection methods in noisy environment on publicly available ASD Dataset. The performance of the methods is evaluated in terms of Precision, Recall and F-measure and Area under the curve (AUC). It has been observed that there is no clear winner but the methods proposed by Liu et al. and Harel et al. are better in comparison to other methods.
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Kumar, N., Singh, M., Govil, M.C., Pilli, E.S., Jaiswal, A. (2016). Salient Object Detection in Noisy Images. In: Khoury, R., Drummond, C. (eds) Advances in Artificial Intelligence. Canadian AI 2016. Lecture Notes in Computer Science(), vol 9673. Springer, Cham. https://doi.org/10.1007/978-3-319-34111-8_15
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DOI: https://doi.org/10.1007/978-3-319-34111-8_15
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