recognition image analysis and computer vision has always been important in industrial applications with the popularization of cell phones with powerful cameras and internet connectionsthey are also increasingly being generated by the users thereforethere are opportunities to make use of this to provide better user experience in this we will look at how to apply techniques you have learned in the rest of the book to this specific type of data in particularwe will learn how to use the mahotas computer vision package to preprocess images using traditional image-processing functions these can be used for preprocessingnoise removalcleanupcontrast stretchingand many other simple tasks we will also look at how to extract features from images these can be used as input to the same classification methods we have learned about in other we will apply these techniques to publicly available datasets of photographs introducing image processing from the point of view of the computeran image is large rectangular array of pixel values we wish to either process this image to generate new or better image (perhaps with less noiseor with different lookthis is typically the area of image processing we may also want to go from this array to decision that is relevant to our applicationwhich is better known as computer vision not everybody agrees with this distinction of the two fieldsbut its description is almost exactly how the terms are typically used