• Journal of Internet Computing and Services
• /
• v.21 no.2
• /
• pp.65-72
• /
• 2020

In this paper, a USB module with fingerprint recognition was designed as a distributed node of blockchain on distributed ID (DID, distributed ID) for user identification. This biometric-linked fingerprint recognition device was verified for the real-time authentication process of authentication transaction with FIDO(Fast IDentity Online) server. Blockchain DID-based services were proposed like as a method of individual TV rating survey, and recommending service for customized shopping channels, and crypto-currency, too. This DID based remote service can be improved by recognizing of channel-changing information through personal identification. The proposed information of production purchase can be shared by blockchain. And customized service can be provided for the utilization of purchase history in shoppingmall using distributed ID. As a result, this blockchain node-device and Samsung S10 Key-srore with FIDO service can be certified for additional transactions through various biometric authentication like fingerprint, and face recognition.

• The Korean Journal of Food And Nutrition
• /
• v.24 no.3
• /
• pp.386-395
• /
• 2011

The purpose of this research was to study food behaviors and nutrient intakes according to body mass index(BMI) and body image recognition in 211 female university students in Incheon. The majority of the surveyed subjects were in the normal range for BMI. Most of these female university students preferred a thin body type and were not satisfied with their body shapes. Most also controlled their body weight for appearance by exercising and limiting food intake. The obese group often ate processed foods(p<0.01) and ate out(p<0.05). The underweight group and normal-weight group took vitamins and supplements more frequently(p<0.001). Those students who recognized their body image as a 'fat shape' had good appetites(p<0.05) and those who recognized themselves as 'normal shape' considered food formulations ate every meal (p<0.05) and consumed vitamins and other supplements frequently(p<0.01). The mean calorie intake of all students was about 80% of the recommend amount, so there was a risk of lack of various nutrients. The 'fat' students by body image recognition had lower calorie intakes in order to reduce body weight. In all the groups, there was a lack of vitamins $B_1$ and $B_2$, as well as the minerals Ca and Fe. Therefore, education on correct body image recognition and training on proper weight control are deemed necessary. In addition, education and counseling on nutrition that are tailored to individual status are needed.

• Journal of the Korean Institute of Telematics and Electronics C
• /
• v.35C no.6
• /
• pp.76-87
• /
• 1998

This paper deals with a system which recognizes dynmic hand gestures, Korean Sign Language(KSL), mixed with static hand gesture, Korean Manual Alphabet(KMA), continuously. Recognition of continuous hand gestures is very difficult for lack of explicit tokens indicating beginning and ending of signs and for complexity of each gesture. In this paper, state automata is used for segmenting sequential signs into individual ones, and basic elements of KSL and KMA, which consist of 14 hand directions, 23 hand postures and 14 hand orientations are used for recognition of complex gestures under consideration of expandability. Using a pair of CyberGlove and Polhemus sensor, this system recognizes 131 Korean signs and 31 KMA's in real-time with recognition rate 94.3% for KSL excluding no recognition case and 96.7% for KMA.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2003.10a
• /
• pp.986-989
• /
• 2003

In the steel production line, the molten metal of a furnace is transformed into slab material and then move to the hot strip line, This paper describe about the real time recognition system of material management number, which is marked at the surface of a slab in the steel production line. This recognition processing should be performed before the slab is moved to the hot strip line. This system include following recognition steps. First, we remove noise from the captured slab image by use pre-filter. Second, we extract rough area, which is include slab number and then, we extract individual number area. Finally, we recognize material management number by use KLT(Karhunen-Loeve transform) algorithm. We applied our system to the real slave image, which was captured in the process line. In the results, we recognized slave number to the 94% accuracy.

• Journal of the Korea Society of Computer and Information
• /
• v.13 no.6
• /
• pp.273-278
• /
• 2008

Cars attaching new license plates are increasing after introducing the new format of car license plate in Korea. Therefore, a car new license plate recognition system is required for various fields using automatic recognition of car license plates, automatic parking management systems and arrest of criminal or missing vehicles. In this paper, we proposed an intelligent new car license plate recognition method for the various fields. The proposed method is as follows. First of all, an acquired color image from a surveillance camera is converted to a gray level image and binarized by block binarization method. Second, noises of the binarized image removed by morphological characteristics of cars and then license plate area is extracted. Third, individual characters are extracted from the extracted license plate area using Grassfire algorithm. lastly, the extracted characters are learned and recognized by a fuzzy ART algorithm for final car license plate recognition. In the experiment using 100 car images, we could see that the proposed method is efficient.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.13 no.6
• /
• pp.716-721
• /
• 2003

This paper deals with the iris recognition as one of biometric techniques which are applied to identify a person using his/her behavior or congenital characteristics. The iris of a human eye has a texture that is unique and time invariant for each individual. First, we obtain the feature vector from the 2D iris pattern having a property of size invariant and divide it into 24 sectors which are further through three types of 2D Gabor filters. At the recognition process, we compute the similarity measure based on the correlation values. Here, since we use three different matching values obtained from three different directional Gabor filters and select the maximum value among them, it is possible to minimize the recognition error rate. To show the usefulness of the proposed algorithm, we applied it to a biometric database consisting of 50 iris patterns extracted from 10 subjects and finally get more higher than 90% recognition rate.

• Journal of the Institute of Electronics Engineers of Korea CI
• /
• v.46 no.2
• /
• pp.44-51
• /
• 2009

Text understand in natural images has become an active research field in the past few decades. In this paper, we present an automatic recognition system in Korean signboards with a complex background. The proposed algorithm includes detection, binarization and extraction of text for the recognition of shop names. First, we utilize an elaborate detection algorithm to detect possible text region based on edge histogram of vertical and horizontal direction. And detected text region is segmented by clustering method. Second, the text is divided into individual characters based on connected components whose center of mass lie below the center line, which are recognized by using a minimum distance classifier. A shape-based statistical feature is adopted, which is adequate for Korean character recognition. The system has been implemented in a mobile phone and is demonstrated to show acceptable performance.

• Journal of IKEEE
• /
• v.24 no.1
• /
• pp.120-126
• /
• 2020

We present a user recognition method using human body impulse response signals. The body compositions vary from person to person depending on the portion of water, muscle, and fat. In the body communication study, the body has been interpreted circuit models using capacitance and resistances, and its characteristics are determined by the body compositions. Therefore, the individual body channel is unique and can be used for user recognition. In this paper, we applied pseudo impulse signals to the left hand and recorded received signals from the right hand. The empirical mode decomposition (EMD) method removed noise from the received signals and 10 peak values are extracted. We set the differences between peak amplitudes as a key feature to identify individuals. We collected data from 6 subjects and achieved accuracy of 97.71% for the user recognition application.

• Journal of the Ergonomics Society of Korea
• /
• v.30 no.1
• /
• pp.195-202
• /
• 2011

Objective: The aim of this study is to investigate and review the previous researches about objective measuring fatigue caused by visual stimuli. Also, we analyze possibility of alternative visual fatigue measurement methods using facial expression recognition and gesture recognition. Background: In most previous researches, visual fatigue is commonly measured by survey or interview based subjective method. However, the subjective evaluation methods can be affected by individual feeling's variation or other kinds of stimuli. To solve these problems, signal and image processing based visual fatigue measurement methods have been widely researched. Method: To analyze the signal and image processing based methods, we categorized previous works into three groups such as bio-signal, brainwave, and eye image based methods. Also, the possibility of adopting facial expression or gesture recognition to measure visual fatigue is analyzed. Results: Bio-signal and brainwave based methods have problems because they can be degraded by not only visual stimuli but also the other kinds of external stimuli caused by other sense organs. In eye image based methods, using only single feature such as blink frequency or pupil size also has problem because the single feature can be easily degraded by other kinds of emotions. Conclusion: Multi-modal measurement method is required by fusing several features which are extracted from the bio-signal and image. Also, alternative method using facial expression or gesture recognition can be considered. Application: The objective visual fatigue measurement method can be applied into the fields of quantitative and comparative measurement of visual fatigue of next generation display devices in terms of human factor.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.13 no.10
• /
• pp.1987-1996
• /
• 2009

Recently, the color of vehicle license plate has been changed from green to white. Thus the vehicle plate recognition system used for parking management systems, speed and signal violation detection systems should be robust to the both colors. This paper presents a vehicle license plate recognition system, which works on both of green and white plate at the same time. In the proposed system, the image of license plate is taken from a captured vehicle image by using morphological information. In the next, each character region in the license plate image is extracted based on the vertical and horizontal projection of plate image and the relative position of individual characters. Finally, for the recognition process of extracted characters, PCA(Principal Component Analysis) and LDA(Linear Discriminant Analysis) are sequentially utilized. In the experiment, vehicle license plates of both green background and white background captured under irregular illumination conditions have been tested, and the relatively high extraction and recognition rates are observed.