Conference paper
Using the generalized Radon transform for detection of curves in noisy images
In this paper the discrete generalized Radon transform will be investigated as a tool for detection of curves in noisy digital images. The discrete generalized Radon transform maps an image into a parameter domain, where curves following a specific parameterized curve form will correspond to a peak in the parameter domain.
A major advantage of the generalized Radon transform is that the curves are allowed to intersect. This enables a thresholding algorithm in the parameter domain for simultaneous detection of curve parameters. A threshold level based on the noise level in the image is derived. A numerical example is presented to illustrate the theory
| Language: | English |
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| Publisher: | IEEE |
| Year: | 1996 |
| Pages: | 2221-2225 |
| Proceedings: | 1996 IEEE International Conference on Acoustics, Speech and Signal Processing |
| ISBN: | 0780331923 and 9780780331921 |
| ISSN: | 2379190x and 15206149 |
| Types: | Conference paper |
| DOI: | 10.1109/ICASSP.1996.545862 |
Application software Computer vision Digital images Discrete transforms Gaussian noise Image converters Image processing Noise level Noise robustness Radon transforms Stacking Vectors curve parameters detection digital images discrete Radon transform edge detection generalized Radon transform noisy images numerical example parameter domain parameter estimation threshold level thresholding algorithm
