Detection of linear features in images using radon and Hough transforms

Jun Liu; Clayton V. Stewart

doi:10.1117/12.177739

10 June 1994 Detection of linear features in images using Radon and Hough transforms

Jun Liu, Clayton V. Stewart

Proceedings Volume 2232, Signal Processing, Sensor Fusion, and Target Recognition III; (1994) https://doi.org/10.1117/12.177739
Event: SPIE's International Symposium on Optical Engineering and Photonics in Aerospace Sensing, 1994, Orlando, FL, United States

Abstract

Two algorithms were developed to detect linear or quasi-linear feature in images, one using the windowed Radon transform, and the other using the Hough transfrom. Two images from different types of sensors and with different features were processed using the two algorithms, and the results are compared with each other. The algorithm of the Radon transform yielded a reasonable noise reduction, and retained the major linear features. While using the Hough transform, linear feature plots containing different sets of line segments by taking different combinations of thresholds can be obtained.

Citation Download Citation

Jun Liu and Clayton V. Stewart "Detection of linear features in images using Radon and Hough transforms", Proc. SPIE 2232, Signal Processing, Sensor Fusion, and Target Recognition III, (10 June 1994); https://doi.org/10.1117/12.177739

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