基于形参均匀B样条盈亏修正的图像边缘检测

Edge Detection Based on a Uniform B-Spline With Shape Parameter by Modifying Profit and Loss Data

利用形参均匀B样条平滑公式,建立了一种盈亏修正的图像边缘检测新方法。首先对图像的原型值点进行盈亏修正,进一步减少原始图像和平滑图像之间的残余误差;然后利用形参均匀B样条修匀公式对修正后的图像拟合光滑曲面;最后求拟合后的光滑曲面的一阶导数极值点或二阶导数的零交叉点作为边缘特征点。试验表明,该方法稳定可靠,精度较高,能够很好地去除伪边缘;同时该方法简洁,便于实时处理。

This paper puts forward a novel image edge detection method based on uniform B-spline with shape parameter by modifying profit and loss data. The original image intensity is modified for decreasing the residual error between smooth image and original image. A smooth surface of the digital image is presented by the new modified data. The edge point is detected by either computing the local extreme of the directional derivative or computing zero crossing of the second order directional derivative of the smooth surface. Experiments demonstrate that this algorithm is simple, accurate and reliable. It can wipe off the bogus edge commendably and process the digital image in real time.