Geometric shape recognition based on FAST feature points and Hough transform

Jinchuan Kang; Jun Lu; Xu Zhang; Yuan Cao

doi:10.1117/12.3028982

22 May 2024 Geometric shape recognition based on FAST feature points and Hough transform

Jinchuan Kang, Jun Lu, Xu Zhang, Yuan Cao

Proceedings Volume 13176, Fourth International Conference on Machine Learning and Computer Application (ICMLCA 2023); 1317624 (2024) https://doi.org/10.1117/12.3028982
Event: Fourth International Conference on Machine Learning and Computer Application (ICMLCA 2023), 2023, Hangzhou, China

Abstract

With the rapid development of computer vision and image processing, geometric shape recognition has become a highly regarded research area. This study aims to explore a method that combines the FAST feature point recognition algorithm with the Hough transform for fast and accurate recognition of geometric shapes in images, including lines, circles, and rectangles. The FAST feature point recognition algorithm is known for its speed and robustness in effectively detecting key points in images, while the Hough transform allows mapping these key points into parameter space, enabling us to detect and recognize specific geometric shapes. This research focuses on explaining the principles of the method, presenting experimental results, performance evaluations, and discussing future research directions.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Jinchuan Kang, Jun Lu, Xu Zhang, and Yuan Cao "Geometric shape recognition based on FAST feature points and Hough transform", Proc. SPIE 13176, Fourth International Conference on Machine Learning and Computer Application (ICMLCA 2023), 1317624 (22 May 2024); https://doi.org/10.1117/12.3028982

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