This paper introduces a new method in fingerprint feature extraction based on bit-plane. A bit-plane image requires smaller storage space than a greyscale image. Region of interest (ROI) of a fingerprint image is extr...
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This paper introduces a new method in fingerprint feature extraction based on bit-plane. A bit-plane image requires smaller storage space than a greyscale image. Region of interest (ROI) of a fingerprint image is extracted by using a modified blob analysis method, and then the core point of the ROI is detected for dimension reduction process. Before bit-plane is extracted, the fingerprint image is enhanced by using Fourier transform. Bit-plane 7 of the enhanced image is used as the input for fingerprintmatching with phase-only correlation (POC) function. Experiment results showed that the storage space requirement for a fingerprint database could be reduced up to 87% per image for a bit-plane image compared with a greyscale image. The proposed fingerprint matching algorithm achieves 81.16% of recognition rate on FVC2002-Db1a database and 89.78% on FingerDOS database.
By comparing and analyzing several common indoor positioning system solutions, we found that indoor positioning System based on wireless LAN is superior, in which fingerprint matching algorithm was widely used and had...
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ISBN:
(纸本)9781509022397
By comparing and analyzing several common indoor positioning system solutions, we found that indoor positioning System based on wireless LAN is superior, in which fingerprint matching algorithm was widely used and had a large room to be improved for more precise positioning performance. This paper presents an improved fingerprint matching algorithm, which reduces interference by Gaussian filter, calculates distance more accurately by weighted centroid algorithm. Furthermore, the algorithm improves precision by local prediction model revised by entire prediction model to increase the accuracy of positioning. The proposed algorithm can be widely used in different environment and has strong robustness. Experiments performed on real-world place shows that the result of our system is enhanced more than 26%, as compare to the traditional fingerprint-based WLAN positioning system.
The main aim of this study is to establish an efficient platform for fingerprintmatching for low-quality images. Generally, fingerprintmatching approaches use the minutiae points for authentication. However, it is n...
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The main aim of this study is to establish an efficient platform for fingerprintmatching for low-quality images. Generally, fingerprintmatching approaches use the minutiae points for authentication. However, it is not such a reliable authentication method for low-quality images. To overcome this problem, the current study proposes a fingerprintmatching methodology based on normalised cross-correlation, which would improve the performance and reduce the miscalculations during authentication. It would decrease the computational complexities. The error rate of the proposed method is 5.4%, which is less than the two-dimensional (2D) dynamic programming (DP) error rate of 5.6%, while Lee's method produces 5.9% and the combined method has 6.1% error rate. Genuine accept rate at 1% false accept rate is 89.3% but at 0.1% value it is 96.7%, which is higher. The outcome of this study suggests that the proposed methodology has a low error rate with minimum computational effort as compared with existing methods such as Lee's method and 2D DP and the combined method.
Automatic latent fingerprint identification is beneficial during forensic investigations. Usually, latent fingerprint identification algorithms are used to find a subset of similar fingerprints from those previously c...
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Automatic latent fingerprint identification is beneficial during forensic investigations. Usually, latent fingerprint identification algorithms are used to find a subset of similar fingerprints from those previously captured on databases, which are finally examined by latent examiners. Yet, the identification rate achieved by latent fingerprint identification algorithms is far from those obtained by latent examiners. One approach for improving identification rates is the fusion of the match scores computed with fingerprint matching algorithms using a supervised classification algorithm. This approach fuses the results provided by different lower-level algorithms to improve them. Thus, we propose a fusion of fingerprint matching algorithms using a supervised classifier. Our proposal starts with two different local matchingalgorithms. We substitute their global matchingalgorithms with another independent of the local matching, creating two lower-level algorithms for fingerprintmatching. Then, we combine the output of these lower-level algorithms using a supervised classifier. Our proposal achieves higher identification rates than each lower-level algorithm and their fusion using traditional approaches for most of the rank values and reference databases. Moreover, our fusion algorithm reaches a Rank-1 identification rate of 74.03% and 71.32% matching the 258 samples in the NIST SD27 database against 29,257 and 100,000 references, the two largest reference databases employed in our experiments.
Indoor location-based service is emerging as the crucial application of the Internet of Things, which promotes the advance of relevant technology in the indoor scenario. Several positioning algorithms are proposed for...
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Indoor location-based service is emerging as the crucial application of the Internet of Things, which promotes the advance of relevant technology in the indoor scenario. Several positioning algorithms are proposed for different indoor configurations in recent years. The fingerprint-based indoor positioning algorithm has drawn much attention because of the good positioning performance without additional hardware. However, the false fingerprintmatching frequently incurs due to the complexity of the indoor positioning environment and affects the positioning accuracy. In this article, a principal component analysis (PCA)-assisted indoor positioning algorithm based on the adaptive hierarchical clustering algorithm (PAHC) is proposed, which can improve the positioning accuracy through aggregating the reference points (RPs) and conducting the cluster-based PCA (C-PCA) features extraction. More specifically, a clustering termination method is proposed to obtain reasonable RPs clusters adaptively according to the preset RPs. A two-stage fingerprint matching algorithm is proposed based on the C-PCA to further increase the difference between similar RPs and thus improving the positioning accuracy. To verify the proposed algorithm, an indoor wireless system is established in the practical indoor scenario. The experimental results indicate that the proposed PAHC algorithm can increase the positioning accuracy by 9.3% compared with the conventional fingerprintalgorithm.
A new fingerprintmatching method based on a dual-image template and an improved matchingalgorithm is presented in this paper. The proposed matching method is tested using images from FVC2002 fingerprint databases an...
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ISBN:
(纸本)9781538619377
A new fingerprintmatching method based on a dual-image template and an improved matchingalgorithm is presented in this paper. The proposed matching method is tested using images from FVC2002 fingerprint databases and demonstrates a superior performance compared with fingerprint matching algorithm using single-image template. Compared with other dual-image matchingalgorithms, the proposed algorithm has advantages of easy implementation. By taking advantages of dual-image template and improved matchingalgorithm, the proposed matching method improves matching accuracy and relaxes requirement on fingerprint image quality.
This paper proposes a new method of fingerprint singular points searching algorithm based on fingerprint orientation maps mainly. In these orientation maps, mathematical morphology theory and operations are used to se...
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This paper proposes a new method of fingerprint singular points searching algorithm based on fingerprint orientation maps mainly. In these orientation maps, mathematical morphology theory and operations are used to search the fingerprint's singular points in view of the phenomenon that the change of ridges' direction at the points is the fastest in the whole fingerprint image and the directions of finger ridges which surround the points are symmetric with each other. For obtaining more accuracy result, before obtain the orientation maps, we use db3 wavelet technology to remove the most of fingerprint images' noises in this paper. For the same reason, before the main mathematical morphology operations, we first obtain fingerprint images' binary image models based on the db3-denoise image, and use these models to remove the disturb directions of the image background secondly. Experiments indicate this method is easy to understand, achieve and has a good robustness for the fingerprint's translation and deformation.
作者：
Oh, CSRyu, YKSunMoon Univ
Dept Elect Informat & Commun Engn Tanghchung Myun 336708 Asan Si Chungna South Korea
The minimum spanning tree (MST) matchingalgorithm has been used for searching the partial matching points extracted from fingerprint images. The method, however, has some limitations. To obtain the relationship betwe...
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The minimum spanning tree (MST) matchingalgorithm has been used for searching the partial matching points extracted from fingerprint images. The method, however, has some limitations. To obtain the relationship between the enrolled fingerprints and the input fingerprints the MST is used to generate the tree graph that represents the unique graph for the given minutiae. From the graph, the matching points are estimated. However, the shape of the graph highly depends on the positions of the minutiae. If there are some pseudo minutiae caused by noise, the shape of the graph will be totally different. To overcome the limitations of the MST, we propose the center of rotation method (CRM) that finds true partial matching points. The proposed method is based on the assumption that the input fingerprint minutiae are rigid body. In addition, we employ the polygon wrapping the minutiae for fast matching speed and reliable matching results. In conclusion we have been able to confirm fast performance and high identification ratio by using CRM. (C) 2004 Society of Photo-Optical Instrumentation Engineers.
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