Saliency detection via two-directional 2DPCA analysis of image patches |
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| Affiliation: | 1. China Satellite Maritime Tracking and Control Department, Jiangyin, 214431, China;2. The Key Laboratory, Academy of Equipment, Beijing, 101416, China;3. School of Information System & Management, National University of Defense Technology, Changsha, 410073, China;1. Guru Nanak Dev University College, Kapurthala, Punjab, India;2. National Institute of Technology Jalandhar, India;1. Instituto Tecnológico de Chihuahua, División de Estudios de Posgrado e Investigación, Av. Tecnológico No. 2909, Chihuahua, Chih. 31310, Mexico;2. Centro de Investigaciones en Óptica, A. C. Lomas del Bosque No. 115, Col Lomas del Campestre León, Gto 37150. Mexico;1. Department of Mechanical Engineering, National Cheng Kung University, Tainan, Taiwan;2. Department of Neurology, National Cheng Kung University Hospital, 138 Sheng Li Road, Tainan 704, Taiwan;1. Univ. Orléans, INSA-CVL, PRISME, EA4229, 45072 Orléans, France;2. Université Blaise Pascal, Institut Pascal, UMR CNRS 6602, BP 10448, 63000 Clermont-Ferrand, France;3. Université Paris Est, Laboratoire Navier (ENPC/IFSTTAR/CNRS UMR 8205), ENPC, 6 et 8 avenue Blaise Pascal, 77455 Marne la Vallée Cedex, France |
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| Abstract: | Salient object detection is an important and challenging problem in computer vision. In this paper, we present a model of salient region detection based on the fusion of contrast and distribution, computed by two-directional 2DPCA analysis of image patches under the combination of RGB space, LAB space and YCbCr space. First, non-overlap patches of three layers from the image are obtained in the three color spaces respectively and stacked for the combination of the three sapces in a single layer. For every layer, two-directional, two-dimensional PCA are utilized to realize automatic selection of effective features, then based on the high contrast and compact character of salient object, contrast values and distribution values of image patches are fused to get the saliency map. Finally, three saliency maps for three layers are combined to detect salient object. The experimental results on a publicly available database show that the proposed algorithm performs well and are in line with the human eye observation results. |
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| Keywords: | Salient object detection Two-directional, two-dimensional PCA Contrast value Distribution value |
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