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Proceedings Paper

Contour detection using an improved holistically-nested edge detection network
Author(s): Zheng Xu; Haibo Luo; Bin Hui; Zheng Chang
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Paper Abstract

Recently we have been concerned with locating and tracking targets in aerial videos. Targets in aerial videos usually have weak boundaries due to moving cameras. For the purpose of target detecting, detecting the contour of the target is needed and can help with improving the accuracy of target tracking. Edge detection has assisted in obtaining some advances in this effort. However, noisy images and weak boundary limit the performance of existing contour detecting algorithms. After analyzing the structures and edge maps of a Holistically-nested Edge Detection network, we utilize the highest level side-output and improve the architecture of HED; firstly we cut and resized our images into 400*320 pixels. Secondly, we detected edges using our improved HED network. Finally, the contour of an object is found based on edge detecting in the previous stage. We have significantly decreased time spent by reducing 5 side output layers to only 1 and replacing the fusion layer with a refinement and image processing module which also helps with the result. The experimental results show that our algorithm outperforms the state-of-the-art regarding images with noise and weak boundary.

Paper Details

Date Published: 31 August 2018
PDF: 7 pages
Proc. SPIE 10835, Global Intelligence Industry Conference (GIIC 2018), 1083503 (31 August 2018); doi: 10.1117/12.2503573
Show Author Affiliations
Zheng Xu, Shenyang Institute of Automation (China)
Univ. of Chinese Academy of Sciences (China)
Haibo Luo, Shenyang Institute of Automation (China)
Univ. of Chinese Academy of Sciences (China)
Bin Hui, Shenyang Institute of Automation (China)
Univ. of Chinese Academy of Sciences (China)
Zheng Chang, Shenyang Institute of Automation (China)
Univ. of Chinese Academy of Sciences (China)


Published in SPIE Proceedings Vol. 10835:
Global Intelligence Industry Conference (GIIC 2018)
Yueguang Lv, Editor(s)

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