• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2008.05a
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• pp.111-114
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• 2008

This paper proposes an effective hardware scheme for gabor filter and thinning stage processing of a fingerprint identification algorithm based on minutiae with 80% cycle occupation of 32-bit RISC microprocessor. The algorithm was developed based on minutiae with bifurcation and ending point. The analysis of an algorithm source rode was performed using ARM emulator.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2005.11a
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• pp.299-301
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• 2005

본 연구는 생체정보를 이용하여 개인을 인증하고 확인하기 위한 방법으로 기존 단일 생체인식 기법의 단점을 보완하기 위해 홍채와 얼굴을 이용한 다중생체인식(Multi-Modal Biometrics Recognition)기법을 연구하였다. 중국 홍채 데이터베이스 CASIA(Chinese Academy of Science)에 Gabor Wavelet과 FLDA(Fuzzy Linear Discriminant Analysis)를 사용하여 특징벡터를 획득하였으며, FERET(FERET(Face Recognition Technology) 얼굴영상데이터를 사용하여 FERET 연구에서 매우 우수한 성능을 보인 EBGM알고리듬으로 특징벡터를 획득하였다. 이로부터 얻어진 두 score 값에 대하여 다양한 균등화 과정을 시도해 보았으며, 등록자와 침입자를 구분하기 위한 Fusion Algorithm으로 Bayesian Classifier, Support vector machine, Fisher's linear discriminant를 사용하였다. 또한, 널리 사용되는 방법 중 Weighted Summation을 이용하여 다중생체인식의 성능을 비교해 보았다.

• Proceedings of the KIEE Conference
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• 2009.07a
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• pp.1804_1805
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• 2009

최근 여러 산업 분야에서는 품질의 향상과 생산성을 높이기 위해 자동화 검사 장치 개발이 활발하게 연구 되고 있다. 본 연구에서는 비전을 이용한 신뢰도 높은 슬라브(Slab) 표면 검사 자동화 알고리즘의 전처리 단계인 오실레이션 마크(Oscillation mark) 검출을 목표로 한다. 슬라브 영상의 경우 조업시에 발생하는 산화 물질인 스케일(Scale)이 영상 전체에 분포하고 있으며, 이러한 스케일은 형태적 특징 및 밝기 특징이 일정치 않기 때문에 오실레이션 마크 검출 성능을 저하 시킨다. 따라서 스케일의 영향을 최소화 하고 효과적으로 오실레이션 마크를 검출하기 위해 가버 필터(Gabor filter)와 수직 투영 프로파일(Vertical projection profile)을 이용한 노이즈 제거 방법을 사용한다.

• Proceedings of the Korea Information Processing Society Conference
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• 2010.11a
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• pp.506-509
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• 2010

본 논문에서는 지문과 얼굴정보를 이용한 다중 바이오인식 기술(Multi-modal Biometric Technology)을 이용한 운전면허학원 근태관리 시스템 구현에 대해 논한다. 지문인식은 Neurotechnology사의 Free Fingerprint Verification SDK를 사용하였으며, 얼굴인식은 얼굴검출 단계에 Adaboost, 특징추출 단계에 Gabor Wavelet Transform을 이용하였다. 마지막 단계인 인식단계는 두 특징벡터 간의 유클리디언 거리를 이용한다. 두 바이오정보를 통한 인증(Verification)의 결정여부는 AND규칙을 이용하여 두 가지의 바이오정보 인증과정을 모두 통과하여야만 최종 인증확인이 되도록 구현하였다. 성능테스트는 10명의 적은 테스트 집합을 이용하였으며 지문과 얼굴정보를 각각 이용하였을 때보다 두 정보를 결합하였을 때 더 나은 인식률을 보였다.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.40 no.4
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• pp.256-265
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• 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 the Institute of Convergence Signal Processing
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• v.13 no.3
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• pp.142-149
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• 2012

Various image transformations can be used to compress images, to reduce noises in images and to extract useful features. Watermarking techniques using DCT and DWT have been a lot of research interest in the spread of multimedia contents. In this paper, Gabor cosine and sine transform considered as human visual filter is applied to embedding and extraction of watermarks for digital images. The proposed transform is used for watermarking with fifteen attacks. Randomly normal distributed noises are used as an embedded watermark. To measure the similarity between the embedded watermark and extracted one, a correlation value is computed and furthermore is compared with that of existing DCT method. Correlation values of extracted watermark are computed with randomly normal distributed noise sequences, and the sequence with the largest correlation value is declared as the embedded watermark. Frequency components are divided into various bands. Experimental results for low frequency and mid-frequency bands have shown that the proposed GCST provides a good watermarking algorithm and its performance is better than DCT.

• Journal of the Institute of Convergence Signal Processing
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• v.16 no.4
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• pp.122-128
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• 2015

As multimedia information is spread over cyber networks, problems such as protection of legal rights and original proof of an information owner raise recently. Various image transformations of DCT, DFT and DWT have been used to embed a watermark as a token of ownership. Recently, SVD being used in the field of numerical analysis is additionally applied to the watermarking methods. A watermarking method is proposed in this paper using Gabor cosine and sine transform as well as SVD for embedding and extraction of watermarks for digital images. After delivering attacks such as noise addition, space transformation, filtering and compression on watermarked images, watermark extraction algorithm is performed using the proposed GCST-SVD method. Normalized correlation values are calculated to measure the similarity between embedded watermark and extracted one as the index of watermark performance. Also visual inspection for the extracted watermark images has been done. Watermark images are inserted into the lowest vertical ac frequency band. From the experimental results, the proposed watermarking method using the singular vectors of SVD shows large correlation values of 0.9 or more and visual features of an embedded watermark for various attacks.

• Journal of Industrial Convergence
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• v.17 no.3
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• pp.23-29
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• 2019

Object recognition distinguish objects which are different from each other. But Face recognition distinguishes Identity of Faces with Similar Patterns. Feature extraction algorithm such as LBP, HOG, Gabor is being replaced with Deep Learning. As the technology that identify individual face with machine learning using Deep Learning Technology is developing, The Face Recognition Technology is being used in various field. In particular, the technology can provide individual and detailed service by being used in various offline environments requiring user identification, such as Smart Mirror. Face Recognition Technology can be developed as the technology that authenticate user easily by device like Smart Mirror and provide service authenticated user. In this paper, we present investigation about Face Recognition among various techniques for user authentication and analysis of Python source case of Face recognition and possibility of various service using Face Recognition Technology.

• The Journal of the Korea Contents Association
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• v.11 no.11
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• pp.10-18
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• 2011

Medical asset protection is important in each medical institution especially because of the law on private medical record protection and face recognition for this protection is one of the most interesting and challenging problems. In recognizing human faces, the distortion of face images can be caused by the change of pose, illumination, expressions and scale. It is difficult to recognize faces due to the locations of lights and the directions of lights. In order to overcome those problems, this paper presents an analysis of coefficients of Gabor wavelets, kernel decision, feature point, size of kernel, for face recognition in CCTV surveillance. The proposed method consists of analyses. The first analysis is to select of the kernel from images, the second is an coefficient analysis for kernel sizes and the last is the measure of changes in garbo kernel sizes according to the change of image sizes. Face recognitions are processed using the coefficients of experiment results and success rate is 97.3%. Ultimately, this paper suggests empirical application to verify the adequacy and the validity with the proposed method. Accordingly, the satisfaction and the quality of services will be improved in the face recognition area.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2007.04a
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• pp.386-389
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• 2007

EBGM은 자세와 포즈, 조명 변화에 강인한 얼굴 인식 기법중의 하나이다. 하지만 EBGM을 통한 얼굴 인식 시스템은 얼굴의 특징점을 추출하기 위해 주어지는 초기값에 상당한 영향을 받는다. 이러한 문제를 해결하기 위해서 얼굴의 윤곽 추출에 우수한 성능을 보이는 AAM을 통하여 EBGM의 초기값을 주고 EBGM을 통하여 개선하는 방법을 제안하였었다. 본 논문에서는 등록자마다 다른 경계값을 갖는 방법을 제안한다. 기존의 경계값에 비해 성능의 향상이 어느 정도 이뤄지는가에 대해 다룰 것이다.