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Sensors 2015, 15(10), 26654-26674; doi:10.3390/s151026654

A Biologically-Inspired Framework for Contour Detection Using Superpixel-Based Candidates and Hierarchical Visual Cues

1
School of Automation, Huazhong University of Science & Technology, 1037 Luoyu Road, Wuhan 430074, China
2
Electronic Information School, Wuhan University, 299 Bayi Road, Wuhan 430072, China
*
Author to whom correspondence should be addressed.
Academic Editor: Vittorio M. N. Passaro
Received: 28 July 2015 / Revised: 28 September 2015 / Accepted: 7 October 2015 / Published: 20 October 2015
(This article belongs to the Section Physical Sensors)
View Full-Text   |   Download PDF [2962 KB, uploaded 20 October 2015]   |  

Abstract

Contour detection has been extensively investigated as a fundamental problem in computer vision. In this study, a biologically-inspired candidate weighting framework is proposed for the challenging task of detecting meaningful contours. In contrast to previous models that detect contours from pixels, a modified superpixel generation processing is proposed to generate a contour candidate set and then weigh the candidates by extracting hierarchical visual cues. We extract the low-level visual local cues to weigh the contour intrinsic property and mid-level visual cues on the basis of Gestalt principles for weighting the contour grouping constraint. Experimental results tested on the BSDS benchmark show that the proposed framework exhibits promising performances to capture meaningful contours in complex scenes. View Full-Text
Keywords: contour detection; biologically inspired; candidate set; hierarchical visual cues; Gestalt principles contour detection; biologically inspired; candidate set; hierarchical visual cues; Gestalt principles
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Sun, X.; Shang, K.; Ming, D.; Tian, J.; Ma, J. A Biologically-Inspired Framework for Contour Detection Using Superpixel-Based Candidates and Hierarchical Visual Cues. Sensors 2015, 15, 26654-26674.

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