Fusing Images with Multiple Focuses Using Support Vector Machines
ICANN '02 Proceedings of the International Conference on Artificial Neural Networks
IEEE Transactions on Pattern Analysis and Machine Intelligence
A shadow elimination approach in video-surveillance context
Pattern Recognition Letters
Multi-focus image fusion using pulse coupled neural network
Pattern Recognition Letters
Texture classification using sparse frame-based representations
EURASIP Journal on Applied Signal Processing
Foundations and Trends in Signal Processing
PSIVT'06 Proceedings of the First Pacific Rim conference on Advances in Image and Video Technology
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We introduce a novel method of feature extraction for texture segmentation that relies on multichannel wavelet frames and 2-D envelope detection. We describe and compare two algorithms for envelope detection based on (1) the Hilbert transform and (2) zero crossings. We present criteria for filter selection and discuss quantitatively their effect on feature extraction. The performance of our method is demonstrated experimentally on samples of both natural and synthetic textures