Edge Detection and Ridge Detection with Automatic Scale Selection
International Journal of Computer Vision
Hough transform for feature detection in panoramic images
Pattern Recognition Letters
Image Processing in Catadioptric Planes: Spatiotemporal Derivatives and Optical Flow Computation
OMNIVIS '02 Proceedings of the Third Workshop on Omnidirectional Vision
Markov random fields for catadioptric image processing
Pattern Recognition Letters
Optimal edge detection in two-dimensional images
IEEE Transactions on Image Processing
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In the edge detection, the classical operators based on the derivation are sensitive to noise which causes detection errors. It is even more erroneous in the case of omnidirectional images, due to geometric distortions caused by the used sensors. This paper proposes a statistical method of edge detection invariant to image resolution applied to omnidirectional images without preliminary treatments. It is based on the entropy measure. The authors compared its behavior with existing methods on omnidirectional images and perspectives images. The criteria of comparisons are the parameters of Fram and Deutsch. For omnidirectional images, the authors used two types of neighborhood: fixed and adapted to the parameters of the sensor. The authors compared the results of detection visually. The tests are performed on grayscale images.