Filling gaps in the Hough-transform voting locus for N-dimensional parameter spaces

As naively implemented, the voting procedure for a Hough transform may leave gaps in the voting locus, caused by quantization effects. These gaps adversely affect peak detection. This paper presents a general and efficient algorithm for filling such gaps in any number of dimensions.

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