Abstract
An improved Harris corner detection algorithm is proposed based on Barron operator, since Harris corner detection algorithm has a poor accuracy in positioning complex corner detection and may miss certain real corners. Firstly, the image gradient is calculated by using Barron operator to reduce the calculation errors from Prewitt operator or Sobel operator. Secondly, the centre B-spline function is used to smooth image, filter noise, and retain the corners information better. Thirdly, a non-maximal inhibition and corners sieving method is used to determine whether the detected corners are real corners or not. A square window is centered at the pixel and eliminate the corner if the value of the corner response function is non-maximal in the window. And then divide the test image into several blocks so as to process each block independently, and use a cyclic iterative method to determine the threshold value to make sure that the real corners are accurately selected. Finally, experiments indicate the algorithm has relatively great noise proof ability and is able to extract complex corners effectively.
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