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13 June 2024 Rotated object detection based on improved Hough transform
Hanlin Zhang, Yanzhe Xie, Ningfei Wang, Ruiyu Liu, Wangyang Lin, Zongyan Wen
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Proceedings Volume 13180, International Conference on Image, Signal Processing, and Pattern Recognition (ISPP 2024); 1318047 (2024) https://doi.org/10.1117/12.3033541
Event: International Conference on Image, Signal Processing, and Pattern Recognition (ISPP 2024), 2024, Guangzhou, China
Abstract
Most conventional detection methods are usually with rectangular or square bounding boxes, which may leave out angle information. Therefore, for rotated objects, these detection models become inaccurate. In this paper, based on self-built database, we use mirror image and rotation to expand our data size. Then detect lines and acquire angles of inclination by improved Hough transform. Subsequently, we use an algorithm to filter outliers and estimate direction of objects. According to the aspect ratio of training objects, we utilize rotation angles to predict potential detection boxes and the Non-Maximum Suppression (NMS) algorithm to remove redundant frames for all inclined frames, and get the optimal result. The experimental results show that this method achieve an excellent performance, particularly for symmetric or linear objects and there exists tiny error rate comparing with annual measurement.
(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.
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Hanlin Zhang, Yanzhe Xie, Ningfei Wang, Ruiyu Liu, Wangyang Lin, and Zongyan Wen "Rotated object detection based on improved Hough transform", Proc. SPIE 13180, International Conference on Image, Signal Processing, and Pattern Recognition (ISPP 2024), 1318047 (13 June 2024); https://doi.org/10.1117/12.3033541
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KEYWORDS
Object detection
Hough transforms
Education and training
Edge detection
Computer vision technology
Detection and tracking algorithms
Tunable filters
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