7 June 2018 Multiple Gestalt principles-based graph for salient region detection
Jinxia Zhang, Shixiong Fang, Haifeng Zhao, Guang-Hai Liu, Haikun Wei, Lihuan Chen, Kanjian Zhang
Author Affiliations +
Abstract
Recently, a number of graph-based approaches have been proposed to detect salient regions in images. Although the graph is essential for these approaches, the graph construction method has not been studied in much detail. We propose a graph construction method that makes better use of multiple Gestalt principles. Specifically, spatial proximity, color similarity, and texture similarity between image regions are employed to choose different edges of the graph. Furthermore, the confliction among multiple Gestalt principles is solved using a primal rank support vector machines algorithm to compute the edge weights. Our experimental results on various salient region detection databases with comparisons to representative approaches demonstrate that the proposed graph construction method helps to detect salient objects in images.
© 2018 SPIE and IS&T 1017-9909/2018/$25.00 © 2018 SPIE and IS&T
Jinxia Zhang, Shixiong Fang, Haifeng Zhao, Guang-Hai Liu, Haikun Wei, Lihuan Chen, and Kanjian Zhang "Multiple Gestalt principles-based graph for salient region detection," Journal of Electronic Imaging 27(5), 051227 (7 June 2018). https://doi.org/10.1117/1.JEI.27.5.051227
Received: 15 January 2018; Accepted: 9 May 2018; Published: 7 June 2018
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KEYWORDS
Databases

Spatial analysis

Image segmentation

Fourier transforms

Visualization

Binary data

Control systems

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