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Segmentation with saliency map using colour and depth images
Author(s) -
Lee JiEun,
Park RaeHong
Publication year - 2015
Publication title -
iet image processing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.401
H-Index - 45
eISSN - 1751-9667
pISSN - 1751-9659
DOI - 10.1049/iet-ipr.2014.0044
Subject(s) - artificial intelligence , segmentation , computer science , computer vision , thresholding , image segmentation , pattern recognition (psychology) , saliency map , salient , filter (signal processing) , scale space segmentation , image (mathematics)
This study proposes a segmentation method using colour and depth images, from which saliency map is generated. With saliency map obtained from both images, salient foreground is extracted using adaptive thresholding of the saliency map, which reduces performance degradation of existing methods for images with complex background. Also, to enhance edges of the foreground, an adaptive guided filter is used. Normalised cut segmentation is performed with the extracted and enhanced foreground to separate different objects. Experimental results with three different types of datasets show that the proposed method gives better segmentation results than the existing methods, in which the complex background is well separated from the foreground.

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