Visual Approaches for Handle Recognition

Objects can be identified in images extracting local image descriptors for interesting regions. In this paper, instead of making the handle identification process rely in the keypoint detection/matching process only, we present a method that first extracts from the image a region of interest (ROI) that with high probability contains the handle. This subimage is then processed by the keypoint detection/matching algorithm. Two methods for extracting the ROI are compared, Circle Hough Transform (CHT) and blobs, and combined with three descriptor extraction methods: SIFT, SURF and USURF.

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