Unsupervised texture segmentation using Gabor filters
Pattern Recognition
Filtering for Texture Classification: A Comparative Study
IEEE Transactions on Pattern Analysis and Machine Intelligence
Contour and Texture Analysis for Image Segmentation
International Journal of Computer Vision
Practical Content-Adaptive Subsampling for Image and Video Compression
ISM '06 Proceedings of the Eighth IEEE International Symposium on Multimedia
A two-component model of texture for analysis and synthesis
IEEE Transactions on Image Processing
Nonlinear operator for oriented texture
IEEE Transactions on Image Processing
Comparison of texture features based on Gabor filters
IEEE Transactions on Image Processing
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In many real-world object recognition applications, texture plays a very important role. Much research has gone into texture-based segmentation methods, which focus on finding the boundaries between uniformly textured regions. These methods can be adapted to recognize a specific type of texture. However, many naturally occuring objects have a texture with a high degree of irregularity that complicates their recognition, causing generic algorithms to fail. This paper presents a method to recognize one specific type of natural texture: foliage. Starting from a proven technique to extract texture feature information, a recognition model is constructed that incorporates prior knowledge about this particular texture. The algorithm detects 95% of the foliage areas in real-world video data, with less than 8% false positives.