Classifying images using SVM and HOG

Histogram of Oriented Gradients (HOG) is an algorithm that can be used to describe an image using a vector of floating-point descriptors that correspond to the oriented gradient values extracted from that image. The HOG algorithm is very popular and certainly worth reading about in detail to understand how it is implemented in OpenCV, but, for the purposes of this book and especially this section, we'll just mention that the number of the floating-point descriptors will always be the same when they are extracted from images that have exactly the same size with the same HOG parameters. To better understand this, recall that descriptors extracted from an image using the feature detection algorithms we learned ...

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