![]() ![]() The x and y derivatives of an image (Gradients) are useful because the magnitude of gradients is large around edges and corners due to abrupt change in intensity and we know that edges and corners pack in a lot more information about object shape than flat regions. The principle behind the histogram of oriented gradients descriptor is that local object appearance and shape within an image can be described by the distribution of intensity gradients or edge directions. ![]() A feature descriptor is a representation of an image or an image patch that simplifies the image by extracting useful information from it. Histogram of Oriented Gradients (HOG) is a feature descriptor used in image processing, mainly for object detection. Navneet Dalal and Bill Triggs introduced Histogram of Oriented Gradients(HOG) features in 2005. What is Histogram of Oreinted Gradients (HOG)? ![]()
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