• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.6
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• pp.331-345
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• 2021

Virtual testing is considered a major requirement for the safety verification of autonomous driving functions. For virtual testing, both the autonomous vehicle and the driving environment should be modeled appropriately. In particular, a realistic modeling of the perception sensor system such as the one having a camera and radar is important. However, research on modeling to consistently generate realistic perception results is lacking. Therefore, this paper presents a sensor modeling method to provide realistic object detection results in a MILS (Model in the Loop Simulation) environment. First, the key parameters for modeling are defined, and the object detection characteristics of actual cameras and radar sensors are analyzed. Then, the detection characteristics of a sensor modeled in a simulation environment, based on the analysis results, are validated through a correlation coefficient analysis that considers an actual sensor.

• Journal of Korea Multimedia Society
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• v.15 no.10
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• pp.1196-1204
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• 2012

In this paper, a series of algorithms are proposed for controlling different kinds of multimedia contents and realizing interact between human and computer by using single input device. Human gesture recognition based on NUI is presented firstly in my paper. Since the image information we get it from camera is not sensitive for further processing, we transform it to YCbCr color space, and then morphological processing algorithm is used to delete unuseful noise. Boundary Energy and depth information is extracted for hand detection. After we receive the image of hand detection, PCA algorithm is used to recognize hand posture, difference image and moment method are used to detect hand centroid and extract trajectory of hand movement. 8 direction codes are defined for quantifying gesture trajectory, so the symbol value will be affirmed. Furthermore, HMM algorithm is used for hand gesture recognition based on the symbol value. According to series of methods we presented, we can control multimedia contents by using human gesture recognition. Through large numbers of experiments, the algorithms we presented have satisfying performance, hand detection rate is up to 94.25%, gesture recognition rate exceed 92.6%, hand posture recognition rate can achieve 85.86%, and face detection rate is up to 89.58%. According to these experiment results, we can control many kinds of multimedia contents on computer effectively, such as video player, MP3, e-book and so on.

• Proceedings of the Korean Society of Computer Information Conference
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• 2015.07a
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• pp.19-22
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• 2015

주차는 자동차를 이용하는 사람들의 편리한 이동을 위한 기반 행위에 포함되는 요소이다. 따라서 이러한 주차 문제를 해결하는 다양한 서비스가 존재하나, 이러한 서비스를 제공하는 시스템을 개발하기 위해서는 주차공간의 특성을 고려해야 하는 어려움이 있다. 본 연구에서는 카메라 모듈과 딥러닝 알고리즘을 기반으로 하는 이미지 센싱을 활용하여 기존 시스템의 주차 감지 센서부 구축의 문제점을 개선하며, 주차장 수요가 많은 '러쉬 타임'을 반영하여 주차공간을 안내하고 운전자를 유도하는 주차정보시스템을 개발한다.

• Proceedings of the Korean Society of Computer Information Conference
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• 2019.07a
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• pp.165-166
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• 2019

본 논문은 기존의 강압적인 형태의 한글 교육 선행 학습이 아닌 창의적이고 입체적인 에듀테이먼트 교구인 블록 퍼즐과 아두이노를 이용한 명령 센서, 카메라 반사경을 통한 영상 입력을 통해 ICT 융합형 블록 퍼즐기반의 에듀테인먼트 교구를 설계하고자 한다. 즉, 모바일 콘텐츠를 통해 유아에게 교육을 제시하고 유아는 모바일 콘텐츠와 블록 퍼즐 교구, 명령 센서를 통해 입력 영상을 인식하게 한다. 이러한 블록 퍼즐 기반의 에듀테인먼트 교구를 통해서 한글 학습을 놀이 과정 속에서 창의력과 문제 해결 능력을 키울 뿐 만 아니라 스스로 학습을 이끌어가는 자기주도적 학습 능력을 키울 수 있을 것으로 기대한다.

• Annual Conference of KIPS
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• 2021.11a
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• pp.167-169
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• 2021

본 논문에서는 아두이노와 라즈베리 파이를 기반으로 연동한 스마트 금고 시스템을 제안한다. 기존의 금고와 달리 보안성과 편리성의 취약점을 해결하도록 했다. 아두이노와 라즈베리 파이 기반의 다양한 센서를 이용해 스마트 금고의 보안성과 편리성을 높이도록 제안한다. 구현을 위해 지문인식 센서, RFID 센서, 키 패드, GPS, 충격감지 센서, 파이 카메라, PIR 센서를 사용한다. 또한, 스마트 금고 상태와 조작을 할 수 있는 어플리케이션을 제작해 편리성을 높이도록 했다. 금고 프로토 타입의 외부 재질은 3D 프린팅을 이용하여 제작을 했다.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.2
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• pp.182-189
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• 2014

This paper proposed a framework of recognition and tracking for underwater objects using sonar images as an alternative of underwater optical camera which has the limitation of usage due to turbidity. In Part 1, a design and recognition method for 2D artificial landmark was proposed considering the practical performance of current imaging sonars. In particular, its materials are selected in order to maximize detectability based on characteristics of imaging sonar and ultrasonic waves. It has a simple and omni-directional shape which allows an easy modeling of object, and it includes region based features as identifications. Also, we proposed a real-time recognition algorithm including edge detector, Hough circle transforms, and shape matrix based recognition algorithm. The proposed methods are verified by basin tests using DIDSON.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.1
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• pp.123-129
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• 2017

New mobile phones with high tech-camera and a large size memory have been recently launched and people upload pictures of beautiful scenes or unknown flowers in SNS. This paper develops a flower recognition system that can get information on flowers in the place where mobile communication is not even available. It consists of a registration part for reference flowers and a recognition part based on OpenCV for Android platform. A new color classification method using RGB color channel and K-means clustering is proposed to reduce the recognition processing time. And ORB for feature extraction and Brute-Force Hamming algorithm for matching are used. We use 12 kinds of flowers with four color groups, and 60 images are applied for reference DB design and 60 images for test. Simulation results show that the success rate is 83.3% and the average recognition time is 2.58 s on Huawei ALEUL00 and the proposed system is suitable for a mobile phone without a network.

• Journal of Korea Multimedia Society
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• v.15 no.8
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• pp.1067-1074
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• 2012

In this paper, we proposed a contents of Chinese characters learning based on gesture recognition using HMM(hidden markov model) algorithm. Input image of the system is obtained in 3-dimensional information from the TOF camera, and the method of gesture recognition is consisted of part of forecasting user's posture in two infrared images and part of recognizing gestures from continuous poses. In the communication between human and computer, this system provided convenience that user can manipulate it easily by not using any further equipment but action. Because this system raise immersion and interest by using two large display and various multimedia factor, it can maximize information transmission. The edutainment Chinese character contents proposed in this paper provide educational effect that use can master Chinese character naturally with interest, and it can be expected a synergy effect via content experience because it is based on gesture recognition.

• Journal of the Institute of Convergence Signal Processing
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• v.2 no.1
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• pp.1-11
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• 2001

This paper presents a learning-based approach for the construction of license Plate recognition system. The system consist of three modules. They are respectively, car detection module, license plate recognition module and recognition module. Car detection module detects a car in the given image sequence obtained from the camera with simple color-based approach. Segmentation module extracts the license plate in detect car image using neural network as filters for analyzing the color and texture properties of license plate. Recognition module then reads characters in detected license plate with support vector machine (SVM)-based characters recognizer. The system has been tested from parking lot and tollgate, etc. and have show the following performances on average: Car detect rate 100%, segmentation rate 97.5%, and character recognition rate about 97.2%. Overall system performances is 94.7% and processing time is one sec. Then our propose system does well using real world.

• Journal of the Korea Computer Graphics Society
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• v.24 no.5
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• pp.41-48
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• 2018

The most natural way to increase immersion and provide free interaction in a virtual environment is to provide a gesture interface using the user's hand. However, most studies about hand gesture recognition require specialized sensors or equipment, or show low recognition rates. This paper proposes a three-dimensional DenseNet Convolutional Neural Network that enables recognition of hand gestures with no sensors or equipment other than an RGB camera for hand gesture input and introduces a virtual reality game based on it. Experimental results on 4 static hand gestures and 6 dynamic hand gestures showed that they could be used as real-time user interfaces for virtual reality games with an average recognition rate of 94.2% at 50ms. Results of this research can be used as a hand gesture interface not only for games but also for education, medicine, and shopping.