Using orientation codes for rotation-invariant template matching

A new method for rotation-invariant template matching in gray scale images is proposed. It is based on the utilization of gradient information in the form of orientation codes as the feature for approximating the rotation angle as well as for matching. Orientation codes-based matching is robust for searching objects in cluttered environments even in the cases of illumination fluctuations resulting from shadowing or highlighting, etc. We use a two-stage framework for realizing the rotation-invariant template matching; in the first stage, histograms of orientation codes are employed for approximating the rotation angle of the object and then in the second stage, matching is performed by rotating the object template by the estimated angle. Matching in the second stage is performed only for the positions which have higher similarity results in the first stage, thereby pruning out insignificant locations to speed up the search. Experiments with real world scenes demonstrate the rotation- and brightness invariance of the proposed method for performing object search.