July 2016
Beginner to intermediate
462 pages
9h 14m
English
Content preview from Python Data Analysis Cookbook
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Extracting texture features from images
Texture is the spatial and visual quality of an image. In this recipe, we will take a look at Haralick texture features. These features are based on the co-occurrence matrix (11.5) defined as follows:
In equation 11.5, i and j are intensities, while p and q are positions. The Haralick features are 13 metrics derived from the co-occurrence matrix, some of them given in equation 11.6. For a more complete list, refer to http://murphylab.web.cmu.edu/publications/boland/boland_node26.html (retrieved December 2015).
We will calculate the Haralick features with the mahotas API and apply them to the handwritten digits ...
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