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

机译:基于四边形分形逼近控制点的图像畸变校正算法

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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.
机译:有效的失真数字图像校正是基于机器视觉的目标检测和识别的前提。针对传统的畸变校正算法建模复杂,计算量大,边缘信息丢失等缺点,提出了一种基于四边形分形方法控制点的图像畸变校正算法。该算法以标准晶格图像为测量目标,将数学形态学与滑动即将发生的区域运算相结合,固定在畸变图像的像素质心上,并应用基于四边形分形逼近控制点的逼近来拟合高阶多项式校正模型。对于图像灰度恢复,使用两步一维线性向后映射方法。将该算法应用于TMS320DM6437 DSP,实验结果表明,对于768 * 494像素的图像,校正时间为0.036秒。校正误差在0.31像素以内,有效避免了边缘信息的丢失和空洞现象。

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