• Proceedings of the Korean Information Science Society Conference
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• 2003.10b
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• pp.556-558
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• 2003

본 논문은 위상한정상관법을 이용하여 지문을 인식하는 알고리듬을 제안한다. 이 알고리듬은 유사도를 계산하기 위하여 고속푸리에 변환과 상관함수를 이용한다. 제안된 알고리듬은 동일인의 지문에 대하여 예리한 한 개의 피크만을 나타내므로 지문인식에 대한 명확한 결과를 보여준다. 더욱이 이 방법은 명확하게 입력되지 않은 지문에 대하여도 별도의 복잡한 전처리과정을 거치지 않고도 우수한 성능을 보여 준다. 또한 입력된 지문이 평행이동 한 경우에도 우수한 성능을 보여준다. 실험결과는 제안된 알고리듬이 지문을 인식하는데 효과적임을 보여준다.

• Proceedings of the Korea Multimedia Society Conference
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• 2002.05c
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• pp.277-281
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• 2002

본 논문에서는 '지문 인식의 전처리 과정 단축에 관한 연구'의 알고리즘의 구현에 대한 내용을 언급했으며, 향우 보완에 대한 내용을 다루고 있다[6]. 기존의 알고리즘을 보면 지문 매칭을 하기 전에 이미지 이진화와 세선화, 방향성 추출, 특징점 추출을 거친 후에 지문의 매칭이 이루어지는 단계이다. 이런 단계를 줄이기 위해 논문에서는 세선화 과정에서 기존의 알고리즘을 쓰지 않고 융선을 추적해 나가는 방법으로 세선화를 함과 동시에 방향성 추출과 특징점 추출을 함께 해 나갈 수 있는 방향을 제시하고 있다. 이렇게 됨으로써 인식 시간을 단축 할 수 있다.

• Proceedings of the Korean Information Science Society Conference
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• 2004.04b
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• pp.799-801
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• 2004

본 논문은 위상한정상관법을 이용하여 손상된 지문을 인식할 수 있는 방법을 제안한다. 위상한정상관법은 등록된 사람의 지문에 대하여 등록되지 않은 사람의 지문보다 상대적으로 높은 피크치를 나타내지만, 여러 가지 원인으로 손상된 지문에 대하여도 피크지에 대한 임계치를 찾아냄으로써 입력지문이 등록지문과 동일한지 여부를 판정할 수 있음을 보인다. 실험을 통하여 손상되는 원인별 실험적 임계치를 제시하고, 위상한정상관법과 제안된 임계지 설정방법에 의하여 손상된 지문에 대하여 유효함을 보인다.

• Proceedings of the Korea Information Processing Society Conference
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• 2004.05a
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• pp.695-698
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• 2004

본 논문에서는 지문 입력기로부터 입력된 지문영상에 대한 전처리 과정에서 기존의 단계들인 모폴로지와 이진화 과정 대신에 새로운 에지(Edge) 보정과 땀샘(sweat gland) 보정 방법을 적용하여 여러 잡음들을 빠르면서 효율적으로 제거하는 방법을 제안하고 이에 대한 실험 결과에서 이 제안된 방법이 기존의 방법들보다 빠르고 선명한 세선화 결과를 획득하게 됨을 보여준다.

• Proceedings of the Korea Information Processing Society Conference
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• 2020.11a
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• pp.458-460
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• 2020

최근 여러 IoT 기기 사용이 급증하면서 보안 위협요소가 사회적인 문제로 대두되고 있다. 이러한 IoT 기기에서 사용자 생체정보를 활용해 사용자를 인증하는 시스템은 보편적으로 사용되고 있다. 그 중 지문인식은 스마트폰부터 여러 기기에 탑재되어 있다. 본 논문에서는 지문인식 센서에 온도, 압력, 터치 센서를 추가하는 기법과 군집화, 패턴 학습 알고리즘을 적용하여 위 변조 검출 능력을 향상시키는 방법을 통하여 지문인식에 대한 이상 징후 탐지 방법을 제안하고자 한다.

• Journal of Internet Computing and Services
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• v.21 no.4
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• pp.17-23
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• 2020

Biometric information indicating measurement items related to human characteristics has attracted great attention as security technology with high reliability since there is no fear of theft or loss. Among these biometric information, fingerprints are mainly used in fields such as identity verification and identification. If there is a problem such as a wound, wrinkle, or moisture that is difficult to authenticate to the fingerprint image when identifying the identity, the fingerprint expert can identify the problem with the fingerprint directly through the preprocessing step, and apply the image processing algorithm appropriate to the problem. Solve the problem. In this case, by implementing artificial intelligence software that distinguishes fingerprint images with cuts and wrinkles on the fingerprint, it is easy to check whether there are cuts or wrinkles, and by selecting an appropriate algorithm, the fingerprint image can be easily improved. In this study, we developed a total of 17,080 fingerprint databases by acquiring all finger prints of 1,010 students from the Royal University of Cambodia, 600 Sokoto open data sets, and 98 Korean students. In order to determine if there are any injuries or wrinkles in the built database, criteria were established, and the data were validated by experts. The training and test datasets consisted of Cambodian data and Sokoto data, and the ratio was set to 8: 2. The data of 98 Korean students were set up as a validation data set. Using the constructed data set, five CNN-based architectures such as Classic CNN, AlexNet, VGG-16, Resnet50, and Yolo v3 were implemented. A study was conducted to find the model that performed best on the readings. Among the five architectures, ResNet50 showed the best performance with 81.51%.

• Journal of the Korea Computer Industry Society
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• v.3 no.9
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• pp.1269-1278
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• 2002

The more high growth of knowledge, the more need personal identity technique. Fingerprint or iris of the eye identity techniques are already commercialized and used various field. Using human face recognition or authentication are not high performance yet. But application for an organism or face recognition are expected getting important. We propose a user recognition system by verifying similarity comparison of eye and lip component images which are splitted, calculated characteristic rate of each facial components and added weight to special formula. Through test proposed methods and analysis the result, we got a high recognition rate.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.2
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• pp.892-911
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• 2019

Biometric recognition systems have been widely used for information security. Among the most popular biometric traits, there are fingerprint and face due to their high recognition accuracies. However, the security system that uses face recognition as the login method are vulnerable to face-spoofing attacks, from using printed photo or video of the valid user. In this study, we propose a fast and robust method to detect face-spoofing attacks based on the analysis of spatial frequency differences between the real and fake videos. We found that the effect of a spoofing attack stands out more prominently in certain regions of the 2D Fourier spectra and, therefore, it is adequate to use the information about those regions to classify the input video or image as real or fake. We adopt a divide-conquer-aggregate approach, where we first divide the frequency domain image into local blocks, classify each local block independently, and then aggregate all the classification results by the weighted-sum approach. The effectiveness of the methodology is demonstrated using two different publicly available databases, namely: 1) Replay Attack Database and 2) CASIA-Face Anti-Spoofing Database. Experimental results show that the proposed method provides state-of-the-art performance by processing fewer frames of each video.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.2
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• pp.503-523
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• 2022

Nowadays, many attendance applications utilise biometric techniques such as the face, fingerprint, and iris recognition. Biometrics has become ubiquitous in many sectors. Due to the advancement of deep learning algorithms, the accuracy rate of biometric techniques has been improved tremendously. This paper proposes a web-based attendance system that adopts facial recognition using open-source deep learning pre-trained models. Face recognition procedural steps using web technology and database were explained. The methodology used the required pre-trained weight files embedded in the procedure of face recognition. The face recognition method includes two important processes: registration of face datasets and face matching. The extracted feature vectors were implemented and stored in an online database to create a more dynamic face recognition process. Finally, user testing was conducted, whereby users were asked to perform a series of biometric verification. The testing consists of facial scans from the front, right (30 - 45 degrees) and left (30 - 45 degrees). Reported face recognition results showed an accuracy of 92% with a precision of 100% and recall of 90%.

• Journal of the Microelectronics and Packaging Society
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• v.24 no.4
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• pp.73-77
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• 2017

Recently, fingerprint sensors have widely used for personal information security, and require quality evaluation to reduce an error of their recognition rate. Quality of fingerprint sensors is evaluated by variation of their electrical resistance introducing by contacts between a probe tip and a sensor electrode, Investigation on the materials compatability and structure optimization of probe is required to reduce deformation of sensor electrode for repeatability of quality testing. Nickel, steel(SK4), beryllium copper, and phosphor bronze were considered as probe materials, and beryllium copper was the most appropriate for materials of probe tips, considering indentation and contact resistance while being contacted probe tips on electrodes. Probes of an inspection part were manufactured with the single-unit structure for physical damage prevention and parallel processing capability. Inspection repeatability was evaluated by voltage variation of fingerprint sensors when the specific current was applied. A single-unit inspection part with beryllium copper probe tips showed excellent repeatability within ${\pm}0.003V$ of its voltage variation.