Multichannel Texture Analysis Using Localized Spatial Filters
IEEE Transactions on Pattern Analysis and Machine Intelligence
Unsupervised texture segmentation using Gabor filters
Pattern Recognition
Text segmentation using Gabor filters for automatic document processing
Machine Vision and Applications - Special issue: document image analysis techniques
Texture Segmentation using 2-D Gabor Elementary Functions
IEEE Transactions on Pattern Analysis and Machine Intelligence
Video cataloguing and browsing
VIP '01 Proceedings of the Pan-Sydney area workshop on Visual information processing - Volume 11
ISNN '07 Proceedings of the 4th international symposium on Neural Networks: Part II--Advances in Neural Networks
Unsupervised segmentation of ultrasonic liver images by multiresolution fractal feature vector
Information Sciences: an International Journal
Texture based characterization of liver tumor on computed tomography images
Proceedings of the International Conference & Workshop on Emerging Trends in Technology
Automated defect detection in uniform and structured fabrics using Gabor filters and PCA
Journal of Visual Communication and Image Representation
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The gabor filter approach is recently used in texture analysis. Among the existing applications, people convolve the given texture image with a set of gabor filters with some user-specified parameters. The convolution takes a lot of time because of the large image size and the computational complexity. This paper utilizes the concept of multi-resolution with parameter selection to do texture analysis. The computation time can be significantly reduced by diminishing the image size according to several different sets of parameters. Experiments demonstrate that our strategy is quite efficient compared with the traditional gabor filter.