• Journal of Information Processing Systems
• /
• v.13 no.4
• /
• pp.852-862
• /
• 2017

In this work a Discrete Cosine Transform (DCT)-based feature dimensionality reduced approach for fingerprint matching is proposed. The DCT is applied on a small region around the core point of fingerprint image. The performance of our proposed method is evaluated on a small database of Bologna University and two large databases of FVC2000. A dimensionally reduced feature vector is formed using only approximately 19%, 7%, and 6% DCT coefficients for the three databases from Bologna University and FVC2000, respectively. We compared the results of our proposed method with the discrete wavelet transform (DWT) method, the rotated wavelet filters (RWFs) method, and a combination of DWT+RWF and DWT+(HL+LH) subbands of RWF. The proposed method reduces the false acceptance rate from approximately 18% to 4% on DB1 (Database of Bologna University), approximately 29% to 16% on DB2 (FVC2000), and approximately 26% to 17% on DB3 (FVC2000) over the DWT based feature extraction method.

• Journal of Digital Contents Society
• /
• v.2 no.2
• /
• pp.179-189
• /
• 2001

This paper aims at faster processing and retrieval in fingerprint identification systems by reducing the amount of preprocessing and the size of the feature vector. The distribution of fingerprint directions is a set of local directions of ridges and furrows in small overlapped blocks in a fingerprint image. It is extracted initially as a set of 8-direction components through the Gabor filter bank. The discontinuous distribution of directions is smoothed to a continuous one and visualized as a direction image. Then the center of the distribution is selected as a reference point. A feature vector is composed of 192 sine values of the ridge angles at 32-equiangular positions with 6 different distances from the reference point in the direction image. Experiments show that the proposed algorithm performs the same level of correct identification as a conventional algorithm does, while speeding up the overall processing significantly by reducing the length of the feature vector.

• Journal of the Korea Institute of Information Security & Cryptology
• /
• v.18 no.4
• /
• pp.93-102
• /
• 2008

Fingerprint sensor interoperability refers to the ability of a system to compensate for the variability introduced in the finger data of individual due to the deployment of different sensors. The purpose of this paper is the development of a compensation algorithm by which the interoperability of fingerprint recognition can be improved among various different fingerprint sensors. In this paper we show that a simple transformation derived to form a Taylor series expansion can be used in conjunction with a set of corresponding minutia points to improve the correspondence of finer fingerprint details within a fingerprint image. This is demonstrated by an applying the transformation to a database of fingerprint images and examining the minutiae match scores with and without the transformation. The EER of the proposed method was improved by average 60.94% better than before compensation.

• Journal of the Korea Institute of Information Security & Cryptology
• /
• v.19 no.1
• /
• pp.125-133
• /
• 2009

Security of biometric data is particularly important as the compromise of the data will be permanent. To protect the biometric data, we need to store it in a non.invertible transformed version. Thus, even if the transformed version is compromised, its valid biometric data are securely remained. Fuzzy vault mechanism was proposed to provide cryptographic secure protection of critical data(e.g., encryption key) with the fingerprint data in a way that only the authorized user can access the critical data by providing the valid fingerprint. However, all the previous results cannot operate on the fingerprint image with a few minutiae, because they use fixed degree of the polynomial without considering the number of fingerprint minutiae. To solve this problem, we use adaptive degree of polynomial considering the number of minutiae. Also, we apply multiple polynomials to operate the fingerprint with a few minutiae. Based on the experimental results, we confirm that the proposed approach can enhance the security level and verification accuracy.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2013.05a
• /
• pp.795-797
• /
• 2013

This paper describes a charge sharing capacitive-sensing circuit technique that improves the quality of images captured with fingerprint sensor LSIs. When the finger is dry, the electrical resistance of a finger surface is high. It leads to poor image quality. To capture clear images even when the finger is dry, the modified capacitive detection circuit improves the image quality using an enhancement plate at the finger surface and a voltage control circuit. The test circuit is analyzed on $0.35{\mu}m$ CMOS process.

• Proceedings of the IEEK Conference
• /
• 2007.07a
• /
• pp.237-238
• /
• 2007

Fingerprint verification based on minutiae mostly has used because it stores a few data and is good for speed. However personal verification errors are caused by extracted from false minutiae. Therefore, in this paper, we propose a new methodology performing together based on image and minutiae. As the result of performing with image and minutiae, false accept rate and false reject rate are improved.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.65 no.6
• /
• pp.1060-1069
• /
• 2016

In this paper, we introduce the fingerprint recognition system based on Radial Basis Function Neural Network(RBFNN). Fingerprints are classified as four types(Whole, Arch, Right roof, Left roof). The preprocessing methods such as fast fourier transform, normalization, calculation of ridge's direction, filtering with gabor filter, binarization and rotation algorithm, are used in order to extract the features on fingerprint images and then those features are considered as the inputs of the network. RBFNN uses Fuzzy C-Means(FCM) clustering in the hidden layer and polynomial functions such as linear, quadratic, and modified quadratic are defined as connection weights of the network. Particle Swarm Optimization (PSO) algorithm optimizes a number of essential parameters needed to improve the accuracy of RBFNN. Those optimized parameters include the number of clusters and the fuzzification coefficient used in the FCM algorithm, and the orders of polynomial of networks. The performance evaluation of the proposed fingerprint recognition system is illustrated with the use of fingerprint data sets that are collected through Anguli program.

• Journal of the Institute of Electronics Engineers of Korea SP
• /
• v.40 no.4
• /
• pp.256-265
• /
• 2003

To improve reliability and practicality, a fingerprint-based biometric system needs to be robust to rotations of an input fingerprint and the processing speed should be fast. Accordingly, this paper presents a new filterbank-based fingerprint feature extraction and matching method that is robust to diverse rotations and reasonably fast. The proposed method fast extracts fingerprint features using a directional filter bank, which effectively decomposes an image into several subband outputs Since matching is also performed rapidly based on the Euclidean distance between the corresponding feature vectors, the overall processing speed is so fast. To make the system robust to rotations, the proposed method generates a set of feature vectors considering various rotations of an input fingerprint and then matches these feature vectors with the enrolled single template feature vector. Experimental results demonstrated the high speed of the proposed method in feature extraction and matching, along with a comparable verification accuracy to that of other leading techniques.

• Journal of KIISE:Databases
• /
• v.41 no.4
• /
• pp.199-208
• /
• 2014

In this paper, we represent a system of identification and feature search for scanned comics in consideration of their content characteristics. For creating the feature of the scanned comics, we utilize a method of hierarchical symmetry fingerprinting. Proposed identification and search system is designed to give online service provider, such as Webhard, an immediate identification result under conditions of huge volume of the scanned comics. In simulation part, we analyze the robustness of the identification of the fingerprint to image modification such as rotation and translation. Also, we represent a structure of database for fast matching in feature point database, and compare search performance between other existing searching methods such as full-search and most significant feature search.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.19 no.1
• /
• pp.75-82
• /
• 2009

This paper propose a method to hide not only biometric features in the biometric image such as face and fingerprint for protecting them from unauthorized entity but also information of responsible person expressed as binary image which can be used to identify the responsibility of divulgence. For this, we investigate the recognition rates and bit error rates of extracted responsible person information watermark for the cases of using face and fingerprint images as cover images for fingerprint and face recognition which are the most popular biometric techniques. From these experiments, we confirm that the proposed method can be used for various application requiring to protect personal biometric information