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: demo program a complete fingerprint feature extraction procedures. Including all the algorithms commonly used options.Centralize: binary image, Center Point- Crop: image pruning- Sectorize: Visualization fan- Normalize: normalized input image- Gabor filters: Visualization Gabor Filter- Convolute: Calculation of the input image and Gabor filter convolution- Features: Characteristics of visualization- FingerCode: in the database to join the fingerprint- Check: Fingerprint matching Platform: |
Size: 367616 |
Author:harry |
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Description: proposed filter-based algorithm uses a bank of Gabor filters to capture both local and global details
in a fingerprint as a compact fixed length FingerCode. The fingerprint matching is based on the Euclidean
distance between the two corresponding FingerCodes and hence is extremely fast. We are able to achieve a
verification accuracy which is only marginally inferior to the best results of minutiae-based algorithms
published in the open literature-proposed filter-based algorithm uses a bank of Gabor filters to capture both local and global details
in a fingerprint as a compact fixed length FingerCode. The fingerprint matching is based on the Euclidean
distance between the two corresponding FingerCodes and hence is extremely fast. We are able to achieve a
verification accuracy which is only marginally inferior to the best results of minutiae-based algorithms
published in the open literature Platform: |
Size: 6144 |
Author:Ash_rulerz |
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Search - fingerprint gabor filters