Unsupervised Clustering of Texture Features Using SOM and Fourier Transform
نویسندگان
چکیده
Texture analysis has a wide range of real-world applications. This paper presents a novel technique for texture feature extraction and compares its performance with a number of other existing techniques using a benchmark image database. The proposed feature extraction technique uses 2 D D R transform and self-organizing map (SOM). A combination of 2D-DFT and SOM with optimal parameter settings produced very promising results. The results from large sets of experiments and detailed analysis are included in this paper.
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