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Proceedings Paper

Detection of linear features in images using radon and Hough transforms
Author(s): Jun Liu; Clayton V. Stewart
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Paper 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.

Paper Details

Date Published: 10 June 1994
PDF: 11 pages
Proc. SPIE 2232, Signal Processing, Sensor Fusion, and Target Recognition III, (10 June 1994); doi: 10.1117/12.177739
Show Author Affiliations
Jun Liu, George Mason Univ. (United States)
Clayton V. Stewart, Science Applications International Corp. (United States)


Published in SPIE Proceedings Vol. 2232:
Signal Processing, Sensor Fusion, and Target Recognition III
Ivan Kadar; Vibeke Libby, Editor(s)

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