• Journal of the Korea Society of Computer and Information
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• v.17 no.2
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• pp.31-40
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• 2012

Iris recognition is a biometric technology which can identify a person using the iris pattern. It is important for the iris recognition system to extract the feature which is invariant to changes in iris patterns. Those changes can be occurred by the influence of lights, changes in the size of the pupil, and head tilting. In this paper, we propose a novel method based on Zernike Moment which is robust to rotations of iris patterns. we utilized a selection of Zernike moments for the fast and effective recognition by selecting global optimum moments and local optimum moments for optimal matching of each iris class. The proposed method enables high-speed feature extraction and feature comparison because it requires no additional processing to obtain the rotation invariance, and shows comparable performance to the well-known previous methods.

• Proceedings of the Korea Information Processing Society Conference
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• 2003.05a
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• pp.583-586
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• 2003

보안이 점점 큰 의미를 가지는 요즘, 생체정보를 개인 신분 확인수단으로 이용하려는 연구가 많이 이루어지고 있다 생체정보를 이용한 분야로는 얼굴 인식, 지문 인식, 정맥 인식, 홍채 인식 등이 있는데 그 중에서도 홍채는 패턴의 불변성과 개인의 정보로 이용될 수 있을 정도로 다양한 패턴 형태를 이루고 있다. 이러한 홍채를 이용하여 신분을 인식하기 위해서는 불필요한 영역은 배제하고 인식을 위한 특징만을 가지고 있는 영역을 정확히 찾는 것이 중요하다고 하겠다. 또한 인식 시간의 단축을 위해서 특징 데이터의 크기를 줄이기 위한 방법도 고려되어야 한다. 이 두 가지 문제를 해결하기 위하여 본 논문에서는 홍채의 특징이 가장 많이 분포되어 있는 영역을 찾기 위한 전처리 기법과 인식을 위한 신경망에서 인식시간을 단축하면서 인식률을 높일 수 있는 최적의 신경망 구조를 찾아내는 방법을 제안한다.

• The Journal of the Korea institute of electronic communication sciences
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• v.8 no.6
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• pp.805-814
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• 2013

This paper proposes a robust hand segmentation method using view-invariant characteristic of a wrist-mounted camera, and deals with a hand shape recognition system based on segmented hand information. We actively utilize the advantage of the proposed camera device that provides view-invariant images physically, and segment hand region using a Bayesian rule based on adaptive histograms. We construct HSV histograms from RGB histograms, and update HSV histograms using hand region information from a current image. We also propose a user adaptation method by which hand models gradually approach user-dependent models from user-independent models as the user uses the system. The proposed method was evaluated using 16 Korean manual alphabet, and we obtained increases of 27.91% in recognition success rate.

• KIPS Transactions on Software and Data Engineering
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• v.3 no.9
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• pp.375-380
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• 2014

Under controlled environment, such as fixed viewpoints or consistent illumination, the performance of face recognition is usually high enough to be acceptable nowadays. Face recognition is, however, a still challenging task in real world. SIFT(Scale Invariant Feature Transformation) algorithm is scale and rotation invariant, which is powerful only in the case of small viewpoint changes. However, it often fails when viewpoint of faces changes in wide range. In this paper, we use Affine SIFT (Scale Invariant Feature Transformation; ASIFT) to detect affine invariant local descriptors for face recognition under wide viewpoint changes. The ASIFT is an extension of SIFT algorithm to solve this weakness. In our scheme, ASIFT is applied only to gallery face, while SIFT algorithm is applied to probe face. ASIFT generates a series of different viewpoints using affine transformation. Therefore, the ASIFT allows viewpoint differences between gallery face and probe face. Experiment results showed our framework achieved higher recognition accuracy than the original SIFT algorithm on FERET database.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.43 no.2 s.308
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• pp.11-19
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• 2006

In this paper, we propose a method to estimate camera extrinsic parameter based on projective and permutation invariance point features. Because feature informations in previous research is variant to c.:men viewpoint, extraction of correspondent point is difficult. Therefore, in this paper, we propose the extracting method of invariant point features, and new matching method using similarity evaluation function and Graham search method for reducing time complexity and finding correspondent points accurately. In the calculation of camera extrinsic parameter stage, we also propose two-stage motion parameter estimation method for enhancing convergent degree of LM algorithm. In the experiment, we compare and analyse the proposed method with existing method by using various indoor images to demonstrate the superiority of the proposed algorithms.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.42 no.2 s.302
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• pp.31-38
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• 2005

Recently, Biometrics-based personal identification is regarded as an effective method of person's identity with recognition automation and high performance. In this paper, the palmprint recognition method based on Hu invariant moment is proposed. And the low-resolution(750dpi) palmprint image$(5.5Cm\times5.5Cm)$ is used for the small scale database of the effectual palmprint recognition system. The proposed system is consists of two parts: firstly, the palmprint fixed equipment for the acquisition of the correctly palmprint image and secondly, the algorithm of the efficient processing for the palmprint recognition. And the palmprint identification step is limited 3 times. As a results, when the coefficient is 0.001 then FAR and GAR are $0.038\%$ and $98.1\%$ each other. The authors confirmed that FAR is improved $0.002\%$ and GAR is $0.1\%$ each other compared with [3].

• Journal of Digital Contents Society
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• v.12 no.3
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• pp.279-289
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• 2011

The latest hardware and software techniques are combined to give safe walking guidance and convenient service of realtime walking assistance system for visually impaired person. This system consists of obstacle detection and perception, place recognition, and sign recognition for pedestrian can safely walking to arrive at their destination. In this paper, we exploit the sign object detection system in subway station for sign recognition that one of the important factors of walking assistance system. This paper suggest the adaptive feature map that can be robustly extract the sign object region from complexed environment with light and noise. And recognize a sign using fast zernike moment features which is invariant under translation, rotation and scale of object during walking. We considered three types of signs as arrow, restroom, and exit number and perform the training and recognizing steps through adaboost classifier. The experimental results prove that our method can be suitable and stable for real-time system through yields on the average 87.16% stable detection rate and 20 frame/sec of operation time for three types of signs in 5000 images of sign database.

• Journal of the Korea Society of Computer and Information
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• v.10 no.3 s.35
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• pp.173-182
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• 2005

In this paper, we propose a landmark recognition method which is irrelevant to the camera viewpoint on the navigation for localization. Features in previous research is variable to camera viewpoint, therefore due to the wealth of information, extraction of visual landmarks for positioning is not an easy task. The proposed method in this paper, has the three following stages; first, extraction of features, second, learning and recognition, third, matching. In the feature extraction stage, we set the interest areas of the image. where we extract the corner points. And then, we extract features more accurate and resistant to noise through statistical analysis of a small eigenvalue. In learning and recognition stage, we form robust feature models by testing whether the feature model consisted of five corner points is an invariant feature irrelevant to viewpoint. In the matching stage, we reduce time complexity and find correspondence accurately by matching method using similarity evaluation function and Graham search method. In the experiments, we compare and analyse the proposed method with existing methods by using various indoor images to demonstrate the superiority of the proposed methods.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 1999.05a
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• pp.198-202
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• 1999

최근들어 컴퓨터와 네트워크의 발전으로 일상업무의 대부분을 컴퓨터를 이용하여 할 수 있으므로 신원 확인은 중요한 분야로 부상되었으며, 지문은 편리한 입력과 종생불변하고 만인부동한 특성으로 생체 측정 분야 중 가장 각광받고 있는 분야가 되었으다. 근래에 반도체 지문 입력장치의 개발로 인하여 크기와 속도 문제를 해결하므로써, 키보드, 마우스 등에 부착하여 네트워크의 신원확인과 인증에 많은 수요가 예상된다. 본 논문에서는 반도체 입력 장치를 이용한 지문 인식기술과 암호학을 접목하여 지문을 이용한 신원확인과 인증하여 기본형 보안 시스템 적용에 관해 연구하였다.

• Proceedings of the Korea Society for Industrial Systems Conference
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• 1998.03a
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• pp.305-311
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• 1998

본 논문에서는 회전과 크리에 무관한 상관결과를 얻기 위하여 WCHF-fSDF(wavelet circular harmonic function-filter modulation synthetic discriminant function)필터를 제안하였다. WCHF-fSDF 필터는 기준영상에 대하여 크기변화된 영상들을 웨이브릿 변환한 후, 이들로부터 추출한 단일 원형고조함수를 학습영상으로 사용하여 합성한다. 웨이브릿 변환은 입력영상과 웨이브릿 함수와의 상관으로 정의되므로 웨이브릿 변환을 이용한 패턴인식을 하기 위해서는 두 개의 4f 광 상관 시스템이 필요하다. 여기서 입력영상에 필요한 웨이브릿 함수를 제안된 필터의 설계과정에 포함시켜 전체 광 상관 시스템을 하나의 4f 광상관시스템을 대체시켰다.