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High Quality Content by WIKIPEDIA articles! In computer vision and image processing the concept of feature is used to denote a piece of information which is relevant for solving the computational task related to a certain applicationWhen features are defined in terms of local neighborhood operations applied to an image, a procedure commonly referred to as feature extraction, one can distinguish between feature detection approaches that produce local decisions whether there is a feature of a given type at a given image point or not, and those who produce non-binary data as result. The…mehr

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High Quality Content by WIKIPEDIA articles! In computer vision and image processing the concept of feature is used to denote a piece of information which is relevant for solving the computational task related to a certain applicationWhen features are defined in terms of local neighborhood operations applied to an image, a procedure commonly referred to as feature extraction, one can distinguish between feature detection approaches that produce local decisions whether there is a feature of a given type at a given image point or not, and those who produce non-binary data as result. The distinction becomes relevant when the resulting detected features are relatively sparse. Although local decisions are made, the output from a feature detection step does not need to be a binary image. The result is often represented in terms sets of (connected or unconnected) coordinates of the image points where features have been detected, sometimes with subpixel accuracy.