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A new Wavelet based Edge detection Technique for Iris Imagery

机译:一种新的基于小波的虹膜图像边缘检测技术

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In this paper, we present a novel design of a wavelet based edge detection technique. Edge detection is an important task in image processing. Edges in images can be mathematically defined as local singularities. Until recently, the Fourier transforms was the main mathematical tool for analyzing singularities. However, the Fourier transform is global and not well adapted to local singularities. It is hard to find the location and spatial distribution of singularities with Fourier transforms. Wavelet analysis is a local analysis; it is especially suitable for time frequency analysis, which is essential for singularity detection. The fact motivated us to develop a technique using Haar wavelet to find an edge from an image. The proposed technique has been demonstrated for iris imagery and the reported results have been compared with Daubechies D4 wavelet based edge detection technique.
机译:在本文中,我们提出了一种基于小波的边缘检测技术的新颖设计。边缘检测是图像处理中的重要任务。图像中的边缘可以在数学上定义为局部奇点。直到最近,傅里叶变换是分析奇点的主要数学工具。然而,傅里叶变换是全球性的,不适合局部奇点。很难找到具有傅里叶变换的奇点的位置和空间分布。小波分析是局部分析;它特别适用于时频分析,这对于奇点检测至关重要。事实激励我们使用Haar小波开发一种技术从图像中找到边缘。已经对虹膜图像证明了所提出的技术,并将据报道的结果与基于Duuuchies D4小波的边缘检测技术进行了比较。

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