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指纹图像的质量测量与评价,在指纹图像分割、增强及指纹匹配等环节都有重要应用. 同时,指纹图像的质量分类,对指纹识别算法的适用性研究也有重要意义. 本文提出一种基于支持向量机的指纹图像质量分类方法.该方法选择梯度、Gabor特征、方向对比度等指标,利用支持向量机有效实现指纹图像质量分类. 并采用少类样本合成过采样技术( SMOTE)降低指纹图像质量好坏的类别不平衡问题对分类的影响. 理论分析和实验结果都表明该方法能够较为有效地提高指纹图像质量分类的正确率.-Fingerprint Image Qu
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指纹识别源码,利用梯度法求解指纹的块方向图,很好用-Fingerprint fingerprint source using gradient method with the block pattern well
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给定一个归一化的指纹图像,算法的主要步骤如下:
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** 1 - 将G分成大小为 w x w - (15 x 15) 的块;
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** 2 - 计算每个象素 (i,j)的梯度 dx(i,j) 和 dy(i,j) ,
** 根据计算的需求,梯度算子可以从简单的Sobel算子到复杂的Marr-Hildreth 算子。
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** 3 - 估算优势方向(i,j)-Given a normalized fingerprint image, the algorithm
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指纹图像处理包括梯度处理、方向场处理、平滑处理、智能增强处理等-The fingerprint image processing including gradient processing, direction field processing, smooth processing and intelligent enhancement processing, etc
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指纹图像处理包括梯度处理、方向场处理、平滑处理、智能增强处理等-The fingerprint image processing including gradient processing, direction field processing, smooth processing and intelligent enhancement processing, etc
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指纹图像处理包括梯度处理、方向场处理、平滑处理、智能增强处理等-The fingerprint image processing including gradient processing, direction field processing, smooth processing and intelligent enhancement processing, etc
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指纹图像处理包括梯度处理、方向场处理、平滑处理、智能增强处理等-The fingerprint image processing including gradient processing, direction field processing, smooth processing and intelligent enhancement processing, etc
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指纹图像处理包括梯度处理、方向场处理、平滑处理、智能增强处理等-The fingerprint image processing including gradient processing, direction field processing, smooth processing and intelligent enhancement processing, etc
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指纹模式识别预处理演示(特征点获取)
包括梯度方向场确认 图像分割二值化细化处理 标记特征点演示-Fingerprint pattern recognition preprocessing Demo (feature points to obtain), including the direction of field gradient confirmed the binary segmentation of feature points marked thinning demonstrat
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指纹处理的这个过程代码,有梯度,方向场,分割,均衡,收敛,平滑,增强,二值化,细化和特征点标记的功能。下载即可用.rar-Fingerprint processing of the process code, gradient, direction of the market, segmentation, balance, convergence, smoothing, enhancement, binarization, thinning, and feature points marked
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梯度方向角量化旋转匹配,可用于指纹识别等方面。-Quantify the rotation angle gradient direction matching, can be used for fingerprint identification and other aspects.
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用于指纹检测等,利用图像的梯度方向,获得局部主导方向。Principal Component Analysis (PCA),包含有高斯金字塔分层,SVD奇异值分解,内含测试图像-Used for fingerprint detection, etc. Using the gradient direction of image to get local leading direction. Principal Component Analysis (PCA), contains a gaussi
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MFC实现的指纹识别程序:
实现了:指纹的梯度、方向场、分割、均衡、收敛、平滑、增加、二值化、细 化,标记特征功能!-MFC implementation of the fingerprint identification procedures: to achieve: gradient of fingerprint direction field, split, balanced, convergence, smooth, increasing, binarization, thin
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Sunil Lee and Chang D. Yoo: Video Fingerprinting Based on Centroids of Gradient Orientations
Fingerprints are feature vectors that can uniquely characterize the video signal. The goal of a video fingerprinting system is to judge whether two vide
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指纹识别算法的预处理模块,包括梯度场、方向场、细化、智能增强、二值化、标记等。-Fingerprint recognition algorithm preprocessing module, including gradient field, the direction field, refinement, intelligence enhancement, binary, and other markings.
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梯度法计算指纹方向场,采用了三种方式:1、滑动块 2、自适应块 3、分割固定块(Gradient method is used to calculate the direction field of fingerprint, and three methods are adopted: 1, sliding block 2, adaptive block 3 and segmentation fixed block)
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纹理识别,LTV,通过求梯度,进而求图像的局部总变差,对指纹图像进行纹理提取(Texture recognition, LTV, by seeking gradient, and then find the local image of the total variation, the fingerprint image texture extraction)
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