An image distortion correction algorithm based on quadrilateral fractal approach controlling points

Effective distorted digital image correction is the precondition of target detection and recognition based on machine vision. To overcome traditional distortion correction algorithms' shortcomings, such as complex modeling, massive computation and marginal information loss, an image distortion correction algorithm based on quadrilateral fractal approach controlling points is proposed. This algorithm uses the standard lattice image as the measurement target, combines the mathematical morphology with sliding impending domain operation to fix on the distorted image's pixel centroid, and applies the approach based on quadrilateral fractal approach controlling points to fit high-order polynomial correction model. For image gray recovery, a two-step one-dimensional linear backward mapping method is used. The algorithm was applied on TMS320DM6437 DSP, the experimental results demonstrate that for a 768*494 pixel image, the correction time is 0.036 seconds. The correction error is within 0.31 pixel and the edge information losing and the cavity phenomenon are effectively avoided.