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Name some good texture feature extraction techniques, and why it is good.
An image is basically described by using colour, texture and shape features. There are wide varieties of advanced techniques for the extraction of these features. The Canny Edge Detection, Discrete Wavelet Transform and Gray Level Occurrence Matrix methods are suitable for the efficient texture feature extraction. The Canny edge detection algorithm is mainly concentrated on the edge portion of an image and it can extract texture feature in a good manner. The DWT method is one of the latest texture feature extraction technique. The GLCM method is also good for the extraction of texture feature.
Texture extraction normally used in image classifications and generally it is done by following methods :
Structructered technique
Statistical Technique
Texture Segmentation
Feature extraction to obtain energy, entropy, contrast, inverse difference moment and directional moment. These texture features are served as the input to classify the image accurately. Effective use of multiple features of the image and the selection of a suitable classification method are especially significant for improving classification accuracy.
Optical Character Recognition (OCR) system is best for texture recognition its available in C# library named as EMGUCV its open source and you can use it easily also the examples will be shown to you even you can find out codes of OCR in matlab too and it is based upon the latest techniques of image processing like adjacency, neighbors, regions etc and after that percentage relevance
