we previously used an example of the buildings class here are examples of the text and scene classespattern recognition is just classification of images for historical reasonsthe classification of images has been called pattern recognition howeverthis is nothing more than the application of classification methods to images naturallyimages have their own specific issueswhich is what we will be dealing with in this computing features from images with mahotasit is very easy to compute features from images there is submodule named mahotas features where feature computation functions are available commonly used set of features are the haralick texture features as with many methods in image processingthis method was named after its inventor these features are texture-basedthey distinguish between images that are smooth and those that are patterned and have between different patterns with mahotasit is very easy to compute themharalick_features np mean(mh features haralick(image), the function mh features haralick returns array the first dimension refers to four possible directions in which to compute the features (updownleftand rightif we are not interested in the directionwe can use the mean overall directions based on this functionit is very easy to classify system