CAJ | 학술논문

针对传统图像边缘检测算法存在的边缘方向性不强及边缘较粗等问题，提出了一种基于八方向卷积模板的边缘检测算法。算法采用0°、22.5°、45°、67.5°、90°、112.5°、135°和157.5°八个方向的卷积模板进行边缘检测，模板权值根据中心像素点到邻域像素的距离及方向夹角的大小进行设定，充分考虑到了邻域内像素对中心点方向梯度的贡献大小，能够较好地检测出图像不同的方向边缘。对梯度图像采用了改进的非极大值抑制方法进行细化，可得到单像素的图像边缘。实验结果表明，该算法获取的边缘图像边缘较为完整，方向性强且边缘较细，整体效果明显优于传统Sobel算法。
침대전통도상변연검측산법존재적변연방향성불강급변연교조등문제，제출료일충기우팔방향권적모판적변연검측산법。산법채용0°、22.5°、45°、67.5°、90°、112.5°、135°화157.5°팔개방향적권적모판진행변연검측，모판권치근거중심상소점도린역상소적거리급방향협각적대소진행설정，충분고필도료린역내상소대중심점방향제도적공헌대소，능구교호지검측출도상불동적방향변연。대제도도상채용료개진적비겁대치억제방법진행세화，가득도단상소적도상변연。실험결과표명，해산법획취적변연도상변연교위완정，방향성강차변연교세，정체효과명현우우전통Sobel산법。
An edge detection algorithm based on six directions convolution templates is proposed aiming at the shortcoming of traditional Sobel operator in poor location accuracy and coarse edge. The algorithm uses six direction templates of 0° ,22.5° , 45° ,67.5° ,90° ,112.5° ,135° and 157.5° to detect image edge, considering the contribution of neighborhood pixels for the center pixel in the direction gradient, the templates weights is determined according to the distances and the direction included angle of neighborhood pixel and the center pixel, the different image edge can be detected well. In order to get single pixel width edge, uses improved non-maximum suppression to refine the edge of gradient image. The results show that the new algorithm can detect the image edge relatively complete,with accuracy direction and thinner edge, the whole effects are better than traditional Sobel algorithm.