@inproceedings{c0ac8da9739145b79e15e67d18e01ac3,
title = "Adaptive linear feature detection based on beamlet",
abstract = "Linear feature detection is very important in computer vision, image segmentation and pattern recognition. Traditional Linear feature detectors based on pixel processing each by each may fail to detect out lines in image with low SNR. A fast discrete beamlet transform and an adaptive method of linear feature detection are proposed, which can detect lines with any orientation, location and length. The scale parameter can be adaptively determined by Histogram of beamlet energy function distribution. Experiment results prove the efficiency of the method proposed even in image with very low SNR.",
keywords = "Beamlet transform, Hough transform, Linear feature detection, Radon transform, Wavelet transform",
author = "Shi, {Qin Feng} and Zhang, {Yan Ning}",
year = "2004",
language = "英语",
isbn = "0780384032",
series = "Proceedings of 2004 International Conference on Machine Learning and Cybernetics",
pages = "3981--3984",
booktitle = "Proceedings of 2004 International Conference on Machine Learning and Cybernetics",
note = "Proceedings of 2004 International Conference on Machine Learning and Cybernetics ; Conference date: 26-08-2004 Through 29-08-2004",
}