大鱼际掌纹图像边缘提取算法

Edge extraction algorithm of thenar palmprint image

摘要:

主要研究大鱼际掌纹图像边缘提取算法。介绍几种经典的边缘检测算子以及Hough变换方法，重点讨论了小波模极大值多尺度边缘检测方法。构造了高斯多尺度边缘检测算子，根据噪声和图像边缘的小波变换模值跨尺度传递的不同特征，研究小波模极大值多尺度边缘检测方法，对大鱼际掌纹图像进行边缘提取。实验结果表明该方法检测到的边缘细节丰富，定位较准确，有效降低了噪声，不足之处是连续性较差。

Abstract:

This paper mainly study the edge extraction algorithm of thenar palmprint image. Some classical edge detection operators and Hough transform are introduced. The wavelet modulus maxima multi-scale edge detection method is highlighted. A multi-scale Gaussian edge detector is constructed. According to the characteristics of cross-scale transfer of wavelet transform modules for the noise and the image edge, the method of wavelet modulus maxima multi-scale edge detection is adopted to extract the edge of the thenar palmprint image. The experiment results show that this algorithm can reduce the effects of noise and detect rich edge details; meanwhile, the position of fused edges is precise. Whereas, it has the deficiency of poor continuity at the edges.