• International Journal of Computer Science & Network Security
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• 제24권1호
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• pp.163-177
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• 2024

The fingerprint image quality relies on the clearness of separated ridges by valleys and the uniformity of the separation. The condition of skin still dominate the overall quality of the fingerprint. However, the identification performance of such system is very sensitive to the quality of the captured fingerprint image. Fingerprint image quality analysis and enhancement are useful in improving the performance of fingerprint identification systems. A fuzzy technique is introduced in this paper for both fingerprint image quality analysis and enhancement. First, the quality analysis is performed by extracting four features from a fingerprint image which are the local clarity score (LCS), global clarity score (GCS), ridge_valley thickness ratio (RVTR), and the Global Contrast Factor (GCF). A fuzzy logic technique that uses Mamdani fuzzy rule model is designed. The fuzzy inference system is able to analyse and determinate the fingerprint image type (oily, dry or neutral) based on the extracted feature values and the fuzzy inference rules. The percentages of the test fuzzy inference system for each type is as follow: For dry fingerprint the percentage is 81.33, for oily the percentage is 54.75, and for neutral the percentage is 68.48. Secondly, a fuzzy morphology is applied to enhance the dry and oily fingerprint images. The fuzzy morphology method improves the quality of a fingerprint image, thus improving the performance of the fingerprint identification system significantly. All experimental work which was done for both quality analysis and image enhancement was done using the DB_ITS_2009 database which is a private database collected by the department of electrical engineering, institute of technology Sepuluh Nopember Surabaya, Indonesia. The performance evaluation was done using the Feature Similarity index (FSIM). Where the FSIM is an image quality assessment (IQA) metric, which uses computational models to measure the image quality consistently with subjective evaluations. The new proposed system outperformed the classical system by 900% for the dry fingerprint images and 14% for the oily fingerprint images.

• 제어로봇시스템학회논문지
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• 제20권7호
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• pp.774-781
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• 2014

This paper presents a fingerprint database construction method for WLAN RSSI (Received Signal Strength Indicator)-based indoor positioning. When RSSI is used for indoor positioning, the fingerprint method can achieve more accurate positioning than trilateration and centroid methods. However, a FD (Fingerprint Database) must be constructed before positioning. This step is a very laborious process. To reduce the drawbacks of the fingerprint method, a radio propagation model-based FD construction method is presented. In this method, an FD can be constructed by a simulator. Experimental results show that the constructed FD-based positioning has a 3.17m (CEP) error. In this paper, a spatial correlation method is presented to estimate the NLOS(Non-Line of Sight) error included in the FD constructed by a simulator. As a result, the NLOS error of the FD is reduced and the performance of the error compensated FD-based positioning is improved. The experimental results show that the enhanced FD-based positioning has a 2.58m (CEP) error that is a reasonable performance for indoor LBS (Location Based Service).

• 대한전기학회:학술대회논문집
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• 대한전기학회 2005년도 학술대회 논문집 정보 및 제어부문
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• pp.180-182
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• 2005

Fingerprint-based identification is known to be used for a very long time. Owing to their uniqueness and immutability, fingerprints are today the most widely used biometric features. Therefore, recognition using fingerprints is one of the safest methods as a way of personal identification. But fingerprint identification system has a critical weakness. Since the fingerprint identification time dramatically increase when we compare the unknown fingerprint's minutiae with fingerprint database's minutiae. In this paper, a ridge orientation extraction method using Index table is proposed to solve the problem. The goal of fast direction image extraction is to reduce the identification time and to improve the clarity of ridge and valley structures of input fingerprint image.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• 제24권4호
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• pp.363-374
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• 2020

Fingerprint authentication identifies a user based on the individual's unique fingerprint features. Fingerprint authentication methods are used in various real-life devices because they are convenient and safe and there is no risk of leakage, loss, or oblivion. However, fingerprint authentication methods are often ineffective when there is contamination of the given image through wet, dirty, dry, or wounded fingers. In this paper, a method is proposed to remove noise from fingerprint images using a convolutional neural network. The proposed model was verified using the dataset from the ChaLearn LAP Inpainting Competition Track 3-Fingerprint Denoising and Inpainting, ECCV 2018. It was demonstrated that the model proposed in this paper obtains better results with respect to the methods that achieved high performances in the competition.

• 스마트미디어저널
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• 제3권3호
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• pp.15-19
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• 2014

지문 인식 시스템은 지문인식 장치(fingerprint acquisition device)를 통하여 아날로그(analog) 지문으로부터 변환된 디지털(digital) 지문에서 특이점을 추출하고 추출한 특이점들에 대한 정보를 데이터베이스에 등록하는 오프라인(off-line) 처리와 사용자가 시스템에 접근 할 때 입력한 지문으로부터 특이점을 추출한 후 데이터베이스에 저장되어 있는 특이점들과 정합(matching) 하여 사용자의 시스템 접근 여부를 결정하는 온라인(on-line) 처리로 이루어져 있다. 본 논문에서는 다양한 생체인식시스템 중, 통계 지문 인식 정합 방법인 지문의 특이점 을 사용한다. 좌표를 기준으로서 유사성 거리 측정을 하고, 그리고 특정한 각도, 통계 배포 판에 따라서 지문 인식 모델을 찾는 것이다.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2005년도 추계종합학술대회
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• pp.1007-1010
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• 2005

This paper presents a fingerprint image registration method. In the fingerprint system, the insufficiency of mutual information between a template and a query fingerprint is one of major factors to deteriorate recognition performance. To overcome this problem, we need to register multiple impressions and integrate their information. Our method matches the ridges from multiple impressions recursively and then registers the impressions to minimize the registration error calculated from the Distance map. Our method use regularized TPS model as the transformation model to compensate for the plastic deformation. We compare our method with 3 prior arts (ICP, Distance Map, Ross's method). Our registration error and its' variance is the smallest and also the average registration error is below 3 pixels.

• Journal of Information Processing Systems
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• 제13권4호
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• pp.852-862
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• 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.

• 한국정보통신학회논문지
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• 제8권8호
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• pp.1740-1747
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• 2004

본 논문에서는 지문 융선의 방향정보를 검출하는 효과적인 방법을 제안하였다. 제안방법은 먼저 지문영상을 정규화하고 융선이 있는 전경영역과 융선이 없는 배경영역으로 분할하여 문턱값으로 이진영상으로 변환한다. 전경영역은 융선(ridge)과 골(valley)부분으로 구성되는데 융선의 경계를 런길이 부호를 이용하여 체인코드로 표현한다. 지문 융선의 각 화소에서 방향정보를 검출하기 위해서 체인코드로 표현된 융선 경계를 추적하면서 방향정보를 구한다. 그리고 일정한 블록내의 융선방향은 급격하게 변하지 않으므로 블록별로 평활화하여 각 화소의 방향정보를 구한다. 제안방법의 성능평가를 위해 NIST 및 FVC2002 지문데이터베이스를 이용하여 컴퓨터시뮬레이션을 수행하였다. 실험 결과 제안방법을 지문 융선의 방향정보를 효과적으로 검출하는데 이용할 수 있음을 보였다.

• 대한전자공학회논문지SP
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• 제40권4호
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• pp.248-255
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• 2003

본 논문에서는 상호상관함수를 이용한 지문인식 기법을 제시한다. 본 기법은 특징추출, 지문정렬, 지문매칭으로 구성되는데, 이중에서 본 논문은 새로운 지문정렬 기법을 제안한다. 본 지문정렬 기법에서는 특징점의 융선방향 각도에 대해 상호상관함수를 적용하여 두 지문사이의 회전각도를 구하고, 그후 회전된 지문으로부터 두 지문간의 이동변위를 구하여 지문을 정렬한다. 본 정렬기법은 과도한 탐색에 의존하지 않고 두 지문의 회전각도와 이동변위를 구할 수 있다 제시된 기법으로 지문인식 실험을 한 결과 2.086%의 타인수락오류율(FAR)에 대해 17.299%의 본인거부오류율(FRR)을 얻을 수 있었다.

• 한국통신학회논문지
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• 제14권6호
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• pp.611-620
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• 1989

본 논문에서, PC를 이용하여 개인을 확인할 수 있는 지문정합에 관한 방법을 논하였다. 지문정합법에서 첫째, 지문영상을 세션화하고 단점과 분기점의 위치와 방향으로 구성된 특징점을 추출한다. 지문식별은 추출된 데이터를 이용하여 참조지문과 입력지문의 일치 또는 불일치 판정으로 수행된다. 평활화와 2진화처리, 세션처리후에 세션영상은 정확한 특징량의 추출을 위해 복원처리를 행한다. 정합시에 참조지문과 입력지문사이의 단점과 분기점 위치를 평행이동과 회전이동에 의하여 보상하여 지문확인을 수행한다.