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A matching algorithm for IR/visual images based on the invariant moment of histogram

The concept of invariant moment of gradient orientation histogram and a novel line matching algorithm based on the invariant moment of histogram are proposed to resolve the problem of matching typical objects in the IR and visible images. First, line segments are extracted. Second, the average gradient vector direction of each pixel on the line is adopt as the main direction of the line. Third, the line is divided into non-overlapped sub-regions with the same size. The gradient vector direction of each sub-region are constructed, and the weighted invariant moment of histogram in each sub-region are calculated to build the line descriptor. Finally, the feature matching is realized via the NNDR(nearest/next ratio) method. Experimental results show that the proposed algorithm can match the typical objects in the IR and visible images efficiently and correctly.