• Journal of Information Management
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• v.26 no.1
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• pp.16-51
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• 1995

Information management area faced new challenge arised from the developments of the computer and the information network, and the advent of information super highway. With deep perception of importance of the information, developments of information technologies, and change of the users' environment, we came to envision the digital library. This paper intends to describe the concept and function of the digital library, and to examine some of information technologies such as CD-ROM, OCR technology and image scanning, hypertext, hypermedia and multimedia. And it also considers the strategies for electronic information services and the applicability of the current information technology for digitalization by case studies of the existing database systems.

• Journal of the Institute of Electronics and Information Engineers
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• v.49 no.9
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• pp.300-306
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• 2012

In this paper, we propose a vision based hand motion recognition method for an untouchable user interface of smart devices. First, an original color image is converted into a gray scaled image and its spacial resolution is reduced, taking the small memory and low computational power of smart devices into consideration. For robust recognition of hand motions through separation of horizontal and vertical motions, the horizontal principal area (HPA) and the vertical principal area (VPA) are defined respectively. From the difference images of the consecutively obtained images, the center of gravity (CoG) of the significantly changed pixels caused by hand motions is obtained, and the direction of hand motion is detected by defining the least mean squared line for the CoG in time. For verifying the feasibility of the proposed method, the experiments are carried out with a vision system.

• Journal of Advanced Navigation Technology
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• v.24 no.2
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• pp.155-162
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• 2020

Recently, with the development of computer vision and deep learning technology, research on human action recognition has been actively conducted for video analysis, video surveillance, interactive multimedia, and human machine interaction applications. Diverse techniques have been introduced for human action understanding and classification by many researchers using RGB image, depth image, skeleton and inertial data. However, skeleton-based action discrimination is still a challenging research topic for human machine-interaction. In this paper, we propose an end-to-end skeleton joints mapping of action for generating spatio-temporal image so-called dynamic image. Then, an efficient deep convolution neural network is devised to perform the classification among the action classes. We use publicly accessible UTD-MHAD skeleton dataset for evaluating the performance of the proposed method. As a result of the experiment, the proposed system shows better performance than the existing methods with high accuracy of 97.45%.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.376-378
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• 2022

Artificial intelligence technology is widely used in various fields such as artificial intelligence speakers, artificial intelligence chatbots, and autonomous vehicles. Among these AI application fields, the image processing field shows various uses such as detecting objects or recognizing objects using artificial intelligence. In this paper, data synthesized by a virtual human is used as a method to analyze images taken in a specific space.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.12C
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• pp.1162-1166
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• 2005

A new low dimensional feature representation technique is presented in this paper. Linear discriminant analysis is a popular feature extraction method. However, in the case of high dimensional data, the computational difficulty and the small sample size problem are often encountered. In order to solve these problems, we propose two dimensional direct LDA algorithm, which directly extracts the image scatter matrix from 2D image and uses Direct LDA algorithm for face recognition. The ORL face database is used to evaluate the performance of the proposed method. The experimental results indicate that the performance of the proposed method is superior to DLDA.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2022.06a
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• pp.235-238
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• 2022

본 논문은 인식이 어려운 조명 환경에도 강인한 seven-segment 문자 인식을 위해서, 영상 내에 다양한 조명 연출이 가능하도록 합성 데이터 셋을 생성하고 학습할 수 있는 OCR 방법을 제안한다. 기존 연구에서는 deblurring 과 같이 영상 이미지의 해상도를 높여 문자 인식의 정확도를 향상시키는 것에 초점을 두었으나, 여러 조명 환경에 대비할 수 있는 OCR 관련 연구들은 부족하다. 이를 해결하기 위해 본 논문에서는 문자가 포함된 자연스러운 배경 영상에, seven-segment 문자를 합성시킨 후 relighting 을 적용함으로써 실제 환경과 유사한 장면을 연출해 새로운 합성 데이터 셋을 생성한다. 그리고 생성된 데이터 셋을 딥러닝 기반 학습시켜 다양한 조명에도 강인한 문자 인식기를 만들고자 한다. 합성 데이터 셋의 사용여부와 일반적인 데이터 augmentation 기법의 사용 여부를 비교하여, 본 논문에서 제안한 방법의 효과를 확인할 수 있었다. 이를 통해서 seven-segment 문자 인식 뿐만 아니라, 다양한 문자에 대해서도 적용될 수 있는 초석이 될 것으로 기대된다.

• Journal of Internet Computing and Services
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• v.5 no.5
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• pp.79-91
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• 2004

This paper proposes avatar face generation system that uses shading mechanism and facial features extraction method of facial recognition. Proposed system generates avatar face similar to human face automatically using facial features that extracted from a photo. And proposed system is an approach which compose shade and facial features. Thus, it has advantages that can make more realistic avatar face similar to human face. This paper proposes new eye localization method, facial features extraction method, classification method for minimizing retrieval time, image retrieval method by similarity measure, and realistic avatar face generation method by mapping facial features with shaded face pane.

• The Journal of the Korea institute of electronic communication sciences
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• v.12 no.5
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• pp.883-890
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• 2017

Among the augmented reality services, the most frequently used services are marker based augmented reality services. However, there is a problem that the augmented reality service can not be provided in an environment in which the marker image can not be recognized. In this paper, we propose a method to provide more stable service by estimating the user's posture even if the marker image can not be correctly recognized due to occlusion, obstacle or marker damage in the marker based augmented reality. In the proposed method, when a failure occurs in the provision of a marker based augmented reality, the attitude of the user is estimated using the 3-dimensional coordinates measured through communication between the three beacons and the user, and it allows the user to receive the augmented reality service continuously. We describe the scenario of augmented reality technique using proposed marker recognition and beacon communication, and present the results of experiments based on the degree of occlusion and damage.

• Journal of the Korea Society of Computer and Information
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• v.10 no.4 s.36
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• pp.203-211
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• 2005

In this paper, we propose a new automatic fingerprint identification system that identifies individuals in large databases. The algorithm consists of three steps; preprocessing, classification, and matching, in the classification. we present a new classification technique based on the statistical approach for directional image distribution. In matching, we also describe improved minutiae candidate pair extraction algorithm that is faster and more accurate than existing algorithm. In matching stage, we extract fingerprint minutiaes from its thinned image for accuracy, and introduce matching process using minutiae linking information. Introduction of linking information into the minutiae matching process is a simple but accurate way, which solves the problem of reference minutiae pair selection in comparison stage of two fingerprints quickly. This algorithm is invariant to translation and rotation of fingerprint. The proposed system was tested on 1000 fingerprint images from the semiconductor chip style scanner. Experimental results reveal false acceptance rate is decreased and genuine acceptance rate is increased than existing method.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2003.05a
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• pp.165-170
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• 2003

This paper presents an integrated approach to unconstrained face recognition in arbitrary scenes. The front end of the system comprises of a scale and pose tolerant face detector. Scale normalization is achieved through novel combination of a skin color segmentation and log-polar mapping procedure. Principal component analysis is used with the multi-view approach proposed in[10] to handle the pose variations. For a given color input image, the detector encloses a face in a complex scene within a circular boundary and indicates the position of the nose. Next, for recognition, a radial grid mapping centered on the nose yields a feature vector within the circular boundary. As the width of the color segmented region provides an estimated size for the face, the extracted feature vector is scale normalized by the estimated size. The feature vector is input to a trained neural network classifier for face identification. The system was evaluated using a database of 20 person's faces with varying scale and pose obtained on different complex backgrounds. The performance of the face recognizer was also quite good except for sensitivity to small scale face images. The integrated system achieved average recognition rates of 87% to 92%.