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Proceedings Paper

A cascaded method for transmission tower number recognition in large scenes
Author(s): Yuanchun Xia; Guoyou Wang; Ran Wang; Feng Zhou
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Paper Abstract

Recognizing the transmission tower numbers is an import part of the automatic inspection of high-voltage transmission lines. However, it's infeasible to accomplish this task effectively in one step giving the large scene images shot by unmanned aerial vehicles. In this paper, we present a cascaded framework consists of two CNN components: number plate detection and serial number recognition. The proposed method reduces the difficulty of localizing number characters in large scenes by leveraging the robust background, number plates. On the one hand, the proposed cascaded coarse-to-fine method reduces the missing rate and improves the detection accuracy, on the other hand, the recognition complexity is greatly reduced. The experimental results on our collected dataset demonstrate the effectiveness of the proposed method.

Paper Details

Date Published: 14 February 2020
PDF: 8 pages
Proc. SPIE 11430, MIPPR 2019: Pattern Recognition and Computer Vision, 114301D (14 February 2020); doi: 10.1117/12.2539402
Show Author Affiliations
Yuanchun Xia, Huazhong Univ. of Science and Technology (China)
Guoyou Wang, Huazhong Univ. of Science and Technology (China)
Ran Wang, Huazhong Univ. of Science and Technology (China)
Feng Zhou, Huazhong Univ. of Science and Technology (China)


Published in SPIE Proceedings Vol. 11430:
MIPPR 2019: Pattern Recognition and Computer Vision
Nong Sang; Jayaram K. Udupa; Yuehuan Wang; Zhenbing Liu, Editor(s)

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