Work

Pylon line spatial correlation assisted transmission line detection

Year: 2014

Type: article

Abstract: A transmission line is one of the most hazardous objects to low altitude flying aircraft. Due to its extremely tiny size and unsalient visual features, transmission line detection (TLD) is a well-recognized problem. In this paper, a novel TLD method is proposed with the assistance of the spatial correlation between pylon and line for TLD. First, a unidirectional spatial mapping is built up to describe the pylon line spatial correlation. Then, the proposed pylon line spatial correlation and other line features are integrated into a Bayesian framework, which is trained in advance and used to estimate the probability of one line segment belonging to a transmission line. Compared with three other line-based TLD methods, the experimental results demonstrate that the proposed method can obtain better detection performance with higher detection rates and much lower false alarm rates.

Source: IEEE Transactions on Aerospace and Electronic Systems

DOI: 10.1109/taes.2014.120732

Authors: Jun Zhang, Haotian Shan, Xianbin Cao, Pingkun Yan, Xuelong Li

Institutions: Beihang University, Chinese Academy of Sciences

Language: English

Topic: Advanced Neural Network Applications

Subfield: Computer Vision and Pattern Recognition

Field: Computer Science

Domain: Physical Sciences

SDG: Industry, innovation and infrastructure

Open Access status: green

OpenAlex ID: W1979975384

FWCI: 1.788

Cites: 35

Cited by: 45

Related to: 10