The concept of feature detection is a method to compute abstraction of image information at every point of an image and making local decision at that particular point that there is a feature in an image or not under image processing and computer vision. In this a comparison between three keypoint descriptors have been done and proposed a new combined approach to detect the keypoints present in an image. One of the descriptor is SURF descriptor and other two are new are called BRISK and FREAK. Thus by dividing the time by the number of feature the average time taken for a single feature can be calculated, lesser the number greater is Descriptor in terms of speed and lesser computation power. In the end a flow chart of new proposed methodology is drawn and in future new methodology would be implemented and compare with the other descriptor in my future work.
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