Mr. Qian Zhao Profile

Qian Zhao

at Qingzhou Hi-tech Research Institute

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Proceedings Article | 12 October 2022 Paper

Detecting roads from high-resolution aerial images: a position iteration algorithm for linear target detection

Hao He, Shuyang Wang, Qi Yang, Xu Huang, Qian Zhao

Proceedings Volume 12342, 123420N (2022) https://doi.org/10.1117/12.2644721

KEYWORDS: Roads, Detection and tracking algorithms, Photography, Target detection, Remote sensing, Image resolution, Feature extraction, Unmanned aerial vehicles

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Detecting roads from high-resolution photographs can serve forestry, agriculture, traffic and even military areas, and produce significant social and economic value. In this paper, we present a novel method that utilizes the flatness and the connectivity to detect the road in high-resolution aerial images. The method iterates the probable locations of the roads by using the flatness and connects the roads by using the connectivity. Firstly, we introduce a concept of ‘footprint’, which reveals the probable location and extension direction of a road. Given an initial footprint, we assess the flatness between locations to search the resulting footprint. By iterating and connecting the footprints, our approach produces a set of connected line segments that reflect the road to be detected. In addition, a footprints initialization algorithm is introduced to make our method totally automatic, and a road network pruning algorithm is designed to make the result clearer and more accurate. Tested under three high-resolution aerial photographs, our method achieved an accuracy of more than 80%. The algorithm is adapted for road detection and still linear target detection in high-resolution aerial photographs. Since the algorithm does not require artificial features or training data, it can be quickly deployed in application.

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