Description: 这个算法是仿真linghong的基于指纹码的方法
内有最新的指纹奇异点检测算法-the simulation algorithm is based on fingerprint linghong the code within the latest fingerprint singular point detection Algorithm Platform: |
Size: 669696 |
Author:zhang |
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Description: Cyranose@320便携式电子鼻的检测数据,对象是中药材.在MATLAB上进上气味指纹图谱的分析,其4品种的中药材.结果表明其能将其完全分类.-Cyranose @ 320 portable electronic nose detection data, is of Chinese herbal medicines. In progress on MATLAB odor fingerprint analysis, the 4 species of Chinese herbal medicines. The results show that its able to complete classification. Platform: |
Size: 9216 |
Author:xu |
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Description: 是指纹检测的matlab文件，解压后有一个TXT的文件说明可以，还包含几个图片，非常有用。-Is the fingerprint detection matlab file, after extracting a TXT document that can be, but also contains several pictures, very useful. Platform: |
Size: 604160 |
Author:李奥运 |
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Description: 通过灰度化、分段灰度拉伸、中值滤波、边缘检测和二值化等方式对车牌图像进行预处理，然后基于灰阶跳变定位车牌。-By gray, fractional gray stretch, median filtering, edge detection and binarization, etc. on the license plate image is preprocessed, and then jump on gray positioning plate. Platform: |
Size: 5528576 |
Author:沈静 |
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Description: 提出一种两阶段的奇异点检测方法。将指纹图像分块，求出各块的方向构成块方向图，并在块方向图的基础上利用邻域方向的分
布分析结合改进的Poincare Index方法来确定奇异点所在的候选区域，对候选区域中的像素再通过计算局部方向变化率来确定奇异点的精
确位置。将此方法用于对FVC2004 DB1_A指纹数据库的图像，实验结果表明这种方法对指纹图像中的噪声有很好的鲁棒性，并且计算简
单快速，易于实现。
-A two-phase singularity detection. Fingerprint image block, calculate the direction of each block constitute a block pattern, and pattern in the block based on the use of the distribution of the direction of the neighborhood together with the improved Poincare Index method to determine the singular point where the candidate regions of the candidate region of pixels re-calculated to determine the rate of change of local direction of the precise location of singular points. This method is used to FVC2004 DB1_A fingerprint database of images, experiments show that this method of noise on the fingerprint image has good robustness and computing simple and fast, easy to implement. Platform: |
Size: 123904 |
Author:李辉艳 |
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Description: This code is a complete fingerprint core point detection. It uses orientation field for singular point detection and Zhang-suen algo. for thinning in preprocessing part Platform: |
Size: 68608 |
Author:Gaurav mittal |
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Description: Gabor滤波器经常被用于形状检测和特征提取，比如增强指纹图像。本代码用matlab实现了一个二维Gabor滤波器。
代码使用如下：
function [G,gabout] = gaborfilter1(I,Sx,Sy,f,theta)
from gaborfilter1 with different f(Frequency) and theta(Angle).
for example
f:0,2,4,8,16,32
theta = 0,pi/3,pi/6,pi/2,3pi/4
then for any input image like(eg. stereo.jpg)
you have 6x5 = 30 filtered images.
You can choose your desired angles or frequencies.
You can put nominaly Sx & Sy = 2,4 or some one else.
For instance I tested above example on ( cameraman.tif )(in MATLAB pictures)
I = imread( cameraman.tif )
[G,gabout] = gaborfilter1(I,2,4,16,pi/3)
figure,imshow(uint8(gabout)) -Gabor filters are often used for shape detection and feature extraction, such as the enhanced fingerprint image. Matlab implementation of the code is a two-dimensional Gabor filter. Use the following code: function [G, gabout] = gaborfilter1 (I, Sx, Sy, f, theta) from ' gaborfilter1' with different f (Frequency) and theta (Angle). For example f: 0,2,4, 8,16,32 theta = 0, pi/3, pi/6, pi/2,3 pi/4 then for any input image like (eg. stereo.jpg) you have 6x5 = 30 filtered images. You can choose your desired angles or frequencies. You can put nominaly Sx & Sy = 2,4 or some one else. For instance I tested above example on (' cameraman.tif' ) (in MATLAB pictures) I = imread (' cameraman.tif' ) [G, gabout] = gaborfilter1 (I, 2,4,16, pi/3) figure, imshow (uint8 (gabout)) Platform: |
Size: 1024 |
Author:郑碧波 |
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Description: 基于对指纹的完整脊状结构的显式检测的表征。
在指纹上有丰富的歧视性信息的重要组成部分。当地的脊
结构不能完全以细节为特征。这个基于过滤的算法使用了一个Gabor过滤器来捕获本地和全局的细节。
指纹作为一种紧凑的固定长度的指纹。指纹匹配是基于欧几里德的。
两个对应的指纹之间的距离是非常快的。我们能够实现a。
验证精度仅略低于基于细节的算法的最佳结果。
发表在开放文学。我们的系统比先进的基于细节的系统性能更好。
当应用系统的性能要求不要求非常低的错误接受率时。
最后，我们证明了匹配的性能可以通过结合配对的决定来提高。
基于互补(基于细节和基于过滤的)指纹信息。(With identity fraud in our society reaching unprecedented proportions and with an increasing emphasis on the emerging automatic personal identification applications, biometrics-based verification, especially fingerprint-based identification, is receiving a lot of attention. There are two major shortcomings of the traditional approaches to fingerprint representation. For a considerable fraction of population, the representations based on explicit detection of complete ridge structures in the fingerprint are difficult to extract automatically. The widely used minutiae-based representation does not utilize a significant component of the rich discriminatory information available in the fingerprints.) Platform: |
Size: 1242112 |
Author:kkkaimm |
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