Description: 一个指纹细节点识别的小程序，包括边缘检测，指纹细化，细节点提取和匹配等-a fingerprint minutiae of small identification procedures, including edge detection, fingerprint details, and details of extraction and matching Platform: |
Size: 30361 |
Author:zhaojing |
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Description: 这是一篇利用指纹细节点进行指纹识别（匹配）的比较好的文章，对初学者理解指纹细节点匹配方法有较大帮助。-This is a use of fingerprint minutiae fingerprint identification (match) the relatively good article, for beginners to understand the minutiae matching method is helpful. Platform: |
Size: 171469 |
Author:黄玉 |
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Description: 一个指纹细节点识别的小程序，包括边缘检测，指纹细化，细节点提取和匹配等-a fingerprint minutiae of small identification procedures, including edge detection, fingerprint details, and details of extraction and matching Platform: |
Size: 29696 |
Author:zhaojing |
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Description: 这是一篇利用指纹细节点进行指纹识别（匹配）的比较好的文章，对初学者理解指纹细节点匹配方法有较大帮助。-This is a use of fingerprint minutiae fingerprint identification (match) the relatively good article, for beginners to understand the minutiae matching method is helpful. Platform: |
Size: 171008 |
Author:黄玉 |
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Description: 提出一种新的指纹匹配算法.在配准阶段,引入局部方向场匹配,并结合局部细节点拓扑结构匹配以进行指纹对齐 在对齐后的匹配中,首先在两个指纹的细节点集之间进行弹性匹配,得到一个由匹配的细节点对组成的相集,然后以相似集中的细节点做顶点,以各顶点之间的连线为边,为输入指纹和模板指纹组对应的拓扑图进行图匹配 还引入了全局方向场匹配,并与细节点集匹配进行融合,以提高算法的精度.采用FVC2002公布的指纹库进行对比实验,结果证明了算法的有效性.-A new fingerprint matching algorithm. In the registration phase, the introduction of local orientation field matching, combined with the topology of local minutiae matching for fingerprint alignment in alignment after the match, the first two fingerprint minutiae elastic matching between sets, get the details of a matching set of points on the phase composition, and then focus on the details of the points made similar peak to the connection between the vertices for the edge of the input fingerprint and template fingerprint groups corresponding graphs, graph matching also introduces the global orientation field matching, point set match with the details of the fusion to improve the algorithm accuracy. FVC2002 published fingerprint database using comparative experiment results demonstrate the effectiveness of the algorithm. Platform: |
Size: 333824 |
Author:李辉艳 |
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Description: 一种基于细节点局部描述子的指纹图像匹配方法A local descriptor based on minutiae matching method for fingerprint image-A local descriptor based on minutiae matching method for fingerprint image Platform: |
Size: 276480 |
Author:boyc121 |
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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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Description: 指纹匹配仍然是一个具有挑战性的问题,可靠的人身份验证,因为复杂的扭曲参与两个印象相同的手指。因为绝大多数的指纹匹配算法依赖于细节匹配,细节信息被认为是自动指纹识别系统非常重要的特性。误判率系统的准确性取决于图像质量,图像增强方法、特性提取算法,和以前特性集
-Fingerprint matching is still a challenging problem for reliable person authentication because of the complex distortions involved in two impressions of the same finger. Since the vast majority of fingerprint matching algorithms rely on minutiae matching, minutiae information are regarded as highly significant features for Automatic Fingerprint Recognition System. The accuracy of the AFRS system depends on the image quality, image enhancement methods, feature set extraction algorithms, and feature set pre‐processing/post‐processing algorithms. Platform: |
Size: 4899840 |
Author:小罗 |
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Description: The popular Biometric used to
authenticate a person is Fingerprint which is unique and
permanent throughout a person’s life. A minutia matching is widely used for fingerprint recognition and can be
classified as ridge ending and ridge bifurcation. In this paper we projected Fingerprint Recognition using
Minutia Score Matching method (FRMSM). For Fingerprint
thinning, the Block Filter is used, which scans the
image at the boundary to preserves th
e quality of the image and extract
the minutiae the thinned image.
The false matching ratio is better compared to the existing algorithm-The popular Biometric used to
authenticate a person is Fingerprint which is unique and
permanent throughout a person’s life. A minutia matching is widely used for fingerprint recognition and can be
classified as ridge ending and ridge bifurcation. In this paper we projected Fingerprint Recognition using
Minutia Score Matching method (FRMSM). For Fingerprint
thinning, the Block Filter is used, which scans the
image at the boundary to preserves th
e quality of the image and extract
the minutiae the thinned image.
The false matching ratio is better compared to the existing algorithm Platform: |
Size: 153600 |
Author:ashok |
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Description: This project reflects pattern recognition techniques that we’ve studied in course. Our main focus throughout the project was feature extraction. System extracts minutiae points selected image and then performs fingerprint matching based on minutiae pairing between two provided images-This project reflects pattern recognition techniques that we’ve studied in course. Our main focus throughout the project was feature extraction. System extracts minutiae points selected image and then performs fingerprint matching based on minutiae pairing between two provided images Platform: |
Size: 4275200 |
Author:HAYDAR |
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Description: Latent fingerprint matching has played a critical role in identifying suspects and criminals. However, compared to rolled and plain fingerprint matching, latent identification accuracy is significantly lower due to complex background noise, poor ridge quality and overlapping structured noise in latent images. Accordingly, manual markup of various features (e.g., region of interest, singular points and minutiae) is typically necessary to extract reliable features from latents. To reduce this markup cost and to improve the consistency in feature markup, Platform: |
Size: 89182 |
Author:uud123 |
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Description: —Fingerprint matching systems generally use four types of representation schemes: grayscale image, phase image, skeleton image, and minutiae, among which minutiae-based representation is the most widely adopted one. The compactness of minutiae representation has created an impression that the minutiae template does not contain sufficient information to allow the reconstruction of the original grayscale fingerprint image. This belief has now been shown to be false; several algorithms have been proposed that can reconstruct fingerprint images from minutiae templates. Platform: |
Size: 4903 |
Author:uud123 |
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Search - minutiae matching