基于特征匹配要求的纹理边缘检测

Texture Edge Detection Based on Requirements of Feature Matching

为了更精确地进行机器人双目视觉中的特征匹配,需要获得数字图像中丰富而精确的纹理与边缘信息。为此提出了一种新的基于稳态小波变换(SWT)的多尺度纹理边缘检测算法。利用稳态小波变换(SWT)的平移不变性来精确捕获奇异点,在多尺度上通过小波参数的梯度变化检测纹理边缘,而后进行多尺度融合并运用形态学方法得到单像素宽度、精确的纹理边缘二值图。通过对比实验结果表明,相对于经典的边缘检测算法,该算法在抗噪声能力,物体表面纹理的丰富度以及边缘定位的准确性上有很大的提升,并满足特征匹配的需求。

To gain more accurate feature matching of robot binocular vision,accurate and rich texture and edge information in the digital images is needed.Thus,this paper brings a new multi-scale texture edge detection algorithm based on the stationary wavelet transform （SWT）.This algorithm can capture singular point with the shift-invariance of SWT and detect texture and edge via the gradient changing of multi-scale wavelet coefficients,and then fuse multi-scale texture and edge and use the morphological approach to get single-pixel width,precise texture and edge binary map.By comparing the experimental results show that compared with the classical edge detection methods,this new algorithm obtains a great improvement in the anti-noise capability,the richness of object surface texture and the positioning accuracy of edge.