多梯度融合的RGBD图像边缘检测  

RGBD images edge detection basedon multi-gradient fusion

作　　者：王江明[1] 余烨[1] 金强[1] 李冰飞 

机构地区：[1]合肥工业大学计算机与信息学院,合肥230009

出　　处：《电子测量与仪器学报》2017年第3期436-442,共7页Journal of Electronic Measurement and Instrumentation

基　　金：国家自然科学基金青年基金(61305093);安徽高校省级自然科学研究项目(KJ2014ZD27)资助

摘　　要：基于单一的属性变化进行边缘检测往往会损失部分边缘信息,影响了检测结果的完整性,对此提出一种基于多梯度融合的边缘检测算法。该算法针对RGB图像,首先转换到YCbCr颜色空间下,分别提取亮度分量Y颜色分量Cb、Cr针对提取的亮度分量Y颜色分量Cb、Cr,结合深度图像D,分别使用多方向的圆形边缘检测算子进行梯度计算,对所获得的4种梯度图像进行融合获得边缘检测结果。实验结果表明,算法获得的边缘检测结果更加清晰完整,有效的提高了边缘检测的效果。Some edges cannot be detected when the single property gradient edge detection is used,it affects the integrity of the detection results.To solve the problem,a new edge detection algorithm based on multi-gradient fusion is proposed.The algorithm first converts the RGB image into the YCbCr color space,and then extracts the luminance component Y and the color component Cb,Cr respectively.For the extracted luminance component Y,the color components Cb and Cr,combined with the depth image D,using the multi-directional circular edge detection operator calculates the gradient respectively.The four gradient images are fused to obtain the edge detection results.The experimental results show that the algorithm gains clearer and more complete results,and improves the effect of edge detection effectively.

关 键 词：边缘检测 梯度算子 YCbCr图像 深度图像 多梯度融合 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]