• 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 Korea Academia-Industrial cooperation Society
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• v.21 no.7
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• pp.685-691
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• 2020

In this study, an algorithm that recognizes numbers from 0 to 9 was developed using the data obtained after tracking hand movements using the echo signal of a millimeter-wave radar sensor at 77 GHz. The echo signals obtained from the radar sensor by detecting the motion of a hand gesture revealed a cluster of irregular dots due to the difference in scattering cross-sectional area. A valid center point was obtained from them by applying a K-Means algorithm using 3D coordinate values. In addition, the obtained center points were connected to produce a numeric image. The recognition rate was compared by inputting the obtained image and an image similar to human handwriting by applying the smoothing technique to a CNN (Convolutional Neural Network) model trained with MNIST (Modified National Institute of Standards and Technology database). The experiment was conducted in two ways. First, in the recognition experiments using images with and without smoothing, average recognition rates of 77.0% and 81.0% were obtained, respectively. In the experiment of the CNN model with augmentation of learning data, a recognition rate of 97.5% and 99.0% on average was obtained in the recognition experiment using the image with and without smoothing technique, respectively. This study can be applied to various non-contact recognition technologies using radar sensors.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.15 no.3
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• pp.172-179
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• 2015

Because of the development of computers and high-technology applications, all devices that we use have become more intelligent. In recent years, security and surveillance systems have become more complicated as well. Before new technologies included video surveillance systems, security cameras were used only for recording events as they occurred, and a human had to analyze the recorded data. Nowadays, computers are used for video analytics, and video surveillance systems have become more autonomous and automated. The types of security cameras have also changed, and the market offers different kinds of cameras with integrated software. Even though there is a variety of hardware, their capabilities leave a lot to be desired. Therefore, this drawback is trying to compensate by dint of computer program solutions. Image processing is a very important part of video surveillance and security systems. Capturing an image exactly as it appears in the real world is difficult if not impossible. There is always noise to deal with. This is caused by the graininess of the emulsion, low resolution of the camera sensors, motion blur caused by movements and drag, focus problems, depth-of-field issues, or the imperfect nature of the camera lens. This paper reviews image processing, pattern recognition, and image digitization techniques, which will be useful in security services, to analyze bio-images, for image restoration, and for object classification.

• Journal of Korea Society of Digital Industry and Information Management
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• v.19 no.3
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• pp.213-220
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• 2023

Face recognition is a very important process in video monitoring and is a type of biometric technology. It is mainly used for identification and security purposes, such as ID cards, licenses, and passports. The recognition process has many variables and is complex, so development has been slow. In this paper, we proposed a face recognition method using CNN, which has been re-examined due to the recent development of computers and algorithms, and compared with the feature comparison method, which is an existing face recognition algorithm, to verify performance. The proposed face search method is divided into a face region extraction step and a learning step. For learning, face images were standardized to 50×50 pixels, and learning was conducted while minimizing unnecessary nodes. In this paper, convolution and polling-based techniques, which are one of the deep learning technologies, were used for learning, and 1,000 face images were randomly selected from among 7,000 images of Caltech, and as a result of inspection, the final recognition rate was 98%.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.5
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• pp.251-256
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• 2021

Unlike general cameras, a high-speed camera capable of capturing a large number of frames per second can enable the advancement of some image processing technologies that have been limited so far. This paper proposes a method of removing undesirable noise from an high-speed input color image, and then detecting a human face from the noise-free image. In this paper, noise pixels included in the ultrafast input image are first removed by applying a bidirectional filter. Then, using RetinaFace, a region representing the person's personal information is robustly detected from the image where noise was removed. The experimental results show that the described algorithm removes noise from the input image and then robustly detects a human face using the generated model. The model-based face-detection method presented in this paper is expected to be used as basic technology for many practical application fields related to image processing and pattern recognition, such as indoor and outdoor building monitoring, door opening and closing management, and mobile biometric authentication.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.213-215
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• 2022

Recently, deep learning technology that processes images has been widely used in fire detection, autonomous driving, and defective product detection. In particular, in order to determine whether a product is contaminated or not, it can be identified through the contaminants passed from the existing sensor data, but technologies for recognizing cracks in products or contaminants themselves as images are being actively studied in various fields. In this paper, a system for classifying uncontaminated normal cups and contaminated cups through images was designed and implemented. The image was analyzed using an open image and a photographed image, and the image was analyzed by extracting the upper part of the cup image using Google Objectron for 3D object recognition. Through this study, it is thought that it will be used in various ways for research that can extract the contamination level of products required in the hygiene field based on images.

• Journal of the Korean Society for information Management
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• v.9 no.1
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• pp.131-164
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• 1992

In this study. a technical report management system using optical technology is described in detail. This management system is designed for both bibliographic (character) and full-text (image) information. Several optical filing systems already on the Korean market are scrutinized and compared with standard functions in order to build a more efficient management system for technical reports which can be easily integrated into existing KRISS library automation system. For that purpose, up-to-date technologies (i.e., digital image PI-ocessing (DIP), MARC standards, and optical character recognition (OCR), etc.) are applied to this system.

• Journal of Advanced Navigation Technology
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• v.18 no.3
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• pp.242-247
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• 2014

The advancement of touch user interface technology is mostly due to the debut and success of the new user experience (UX), the iPhone. The introduction of Apple's iPhone especially made possible for the user experience to break away from the traditional input device of the mouse and keyboard. It is advancing from the current 3rd generation touch interface technology into the 4th generation non-touch user interface technology. This paper will present a non-touch interaction technology that allows interaction in a three dimensional setting through 3-D space touch. It will analyze current technologies and future emerging technologies.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.2
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• pp.1083-1088
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• 2014

Recently, due to advances in both imaging technology and ICT, various types of image processing services became available and the application services of these two technologies are diversifying. Recognition of vehicle license plates is used in places where vehicle information is needed such as in parking management. However, existing systems have economic disadvantages like issuing parking tickets and attaching unnecessary equipment. In order to solve these problems, we designed and implemented automatic parking management system through recognition of vehicle license plates by using emguCV that is based on OpenCV. Additionally, we designed improved UI to handle the entire parking management situation which include information such as details of each parking vehicle, parking time and remaining parking spaces without screen movement. This improved UI is implemented with the use of WPF which is the latest technology in user program development. The emguCV used in this paper showed the most optimized performance in Intel based environment. With it, we obtained the result of within 0.5 seconds of recognition processing time and over 90% of recognition rate. Through improved UI, the manager could both simply and intuitively manage the entire system.

• Nuclear Engineering and Technology
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• v.25 no.3
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• pp.424-429
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• 1993

Numeric characters are printed at the end part of nuclear fuel rod containing nuclear pellets. Fuel rods are discriminated and managed systematically by these characters in the process of producing fuel assembly. The characters are also used to examine manufacturing process of fuel rods in the survey of burnup efficiency as well as in inspection of irradiated fuel rod. Therefore automatic character recognition is one of the most important technologies in automatic manufacture of fuel assembly. In this study, character recognition system is developed. In the developed system, mesh feature extracted from each character written in the fuel rod has been compared with reference feature value stored in database, and the character is thus identified. In the result of experiment, 95.83 percent recognition rate is achievable.