摘要
为满足电荷耦合器件(CCD)图像测量系统的快速、高精度测量要求,提出了一种基于改进形态学梯度和Zernike矩算法的图像亚像素边缘检测新方法。基于CCD图像灰度和空间结构信息特点,该算法先利用改进的数学形态学梯度算子进行边缘点的粗定位,在像素级上确定边缘点的坐标和梯度方向;然后再根据构造的边缘点向量和参考阈值,用Zernike矩算法对边缘点进行亚像素的重新定位,实现图像的亚像素边缘检测。仿真图像和实际图像的边缘定位实验结果表明,与Zernike矩、LOG-Zernike矩及Sobel-Zernike矩算法相比,该方法具有更好的定位精度与抗噪性,且检测速度更快。
To satisfy the stringent requirement of measuring accuracy of fast charge coupled device （CCD） measurement system, a novel method is proposed based on improved morphological gradient operator and Zernike moment. According to the CCD image characteristics of pixel gray-scale and spatial structure information, the new method employs improved morphological gradient operator to achieve coarse edge point positioning firstly, and the pixel coordinates of edge points and gradient direction are identified at the same time; then, the edge point is relocated with subpixel accuracy by means of Zeruike moment operator based on the edge point vectors and the reference threshold value ; finally, the sub-pixel edge detection of the image is attained. Edge detection experiments of simulation and natural images were carried out. Compared with the Zernike moment, LOG-Zernike moment and Sobel-Zernike moment algorithms, experiment results show that the proposed method has better performances in positioning accuracy, noise immunity and detection speed.
出处
《仪器仪表学报》
EI
CAS
CSCD
北大核心
2010年第4期838-844,共7页
Chinese Journal of Scientific Instrument
基金
国家自然科学基金(10172043)
国际合作项目(BZ2008060)
山东省自然科学基金(ZR2009CM085)
山东省高等学校科技计划项目(J09LF23)资助
