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A New Bayesian Edge-Linking Algorithm Using Single-Target Tracking Techniques

Center for Information Security Technologies (CIST), Korea University, Seoul 02841, Korea
Academic Editor: Angel Garrido
Symmetry 2016, 8(12), 143; https://doi.org/10.3390/sym8120143
Received: 31 July 2016 / Revised: 14 November 2016 / Accepted: 16 November 2016 / Published: 1 December 2016
This paper proposes novel edge-linking algorithms capable of producing a set of edge segments from a binary edge map generated by a conventional edge-detection algorithm. These proposed algorithms transform the conventional edge-linking problem into a single-target tracking problem, which is a well-known problem in object tracking. The conversion of the problem enables us to apply sophisticated Bayesian inference to connect the edge points. We test our proposed approaches on real images that are corrupted with noise. View Full-Text
Keywords: boundary detection; edge linking; single-target tracking boundary detection; edge linking; single-target tracking
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MDPI and ACS Style

Yoon, J.W. A New Bayesian Edge-Linking Algorithm Using Single-Target Tracking Techniques. Symmetry 2016, 8, 143. https://doi.org/10.3390/sym8120143

AMA Style

Yoon JW. A New Bayesian Edge-Linking Algorithm Using Single-Target Tracking Techniques. Symmetry. 2016; 8(12):143. https://doi.org/10.3390/sym8120143

Chicago/Turabian Style

Yoon, Ji W. 2016. "A New Bayesian Edge-Linking Algorithm Using Single-Target Tracking Techniques" Symmetry 8, no. 12: 143. https://doi.org/10.3390/sym8120143

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