• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.10 no.3
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• pp.16-24
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• 2011

The vehicle electronic control system is being developed as the legal and social demand for ensuring driver's safety is rising. The various Driver Assistance Systems with various sensors such as radars, camera, and lasers are in practical use because of the falling price of hardware and the high performance of sensor and processer. In the preceding study of this research, the program was developed to recognize the experiment vehicle's driving lane and the cars nearby or approaching the experiment vehicle throughout the images taken by CCD camera. In addition, the 'dangerous driving analysis program' which is Vision System basis was developed to analyze the cause and consequence of dangerous driving. However, the Vision system developed in the previous studyhad poor recognition rate of lane and vehicles at the time of passing a tunnel, sunrise, or sunset. Therefore, through mounting the brightness response algorithm to the Vision System, the present study is aimed to analyze the causes of driver's dangerous driving clearly by improving the recognition rate of lane and vehicle, regardless of when and where it is.

• Journal of the Institute of Convergence Signal Processing
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• v.4 no.1
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• pp.56-63
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• 2003

This paper introduces a vision based autonomous mini mobile robot that is an approach to produce real autonomous vehicle. Previous autonomous vehicles are dependent on PC, because of complexity of designing hardware, difficulty of installation and abundant calculations. In this paper, we present an autonomous motile robot system that has abilities of accurate steering, quick movement in high speed and intelligent recognition as a stand-alone system using a mono camera. The proposed system has been implemented on mini track of which width is 25~30cm, and length is about 200cm. Test robot can run at average 32.9km/h speed on straight lane and average 22.3km/h speed on curved lane with 30~40m radius. This system provides a model of autonomous mobile robot adapted a lane recognition algorithm in odor to make real autonomous vehicle easily.

• Journal of the Korea Society of Computer and Information
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• v.25 no.6
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• pp.49-56
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• 2020

The virtual Korean keyboard system is a method of inputting characters by touching a fixed position. This system is very inconvenient for people who have difficulty moving their fingers. To alleviate this problem, this paper proposes an efficient framework that enables keyboard input and handwriting through video and user motion obtained through the RGB camera of the mobile device. To develop this system, we use face recognition to calculate control coordinates from the input video, and develop an interface that can input and combine Hangul using this coordinate value. The control position calculated based on face recognition acts as a pointer to select and transfer the letters on the keyboard, and finally combines the transmitted letters to integrate them to perform the Hangul keyboard function. The result of this paper is an efficient writing system that utilizes face recognition technology, and using this system is expected to improve the communication and special education environment for people with physical disabilities as well as the general public.

• Journal of the Korea Society of Computer and Information
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• v.26 no.3
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• pp.35-42
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• 2021

In this paper, we propose a deep learning-based person re-identification method using a three-dimensional RGB-Depth Xtion2 camera considering joint coordinates and dynamic features(velocity, acceleration). The main idea of the proposed identification methodology is to easily extract gait data such as joint coordinates, dynamic features with an RGB-D camera and automatically identify gait patterns through a self-designed one-dimensional convolutional neural network classifier(1D-ConvNet). The accuracy was measured based on the F1 Score, and the influence was measured by comparing the accuracy with the classifier model (JC) that did not consider dynamic characteristics. As a result, our proposed classifier model in the case of considering the dynamic characteristics(JCSpeed) showed about 8% higher F1-Score than JC.

• Journal of Korea Society of Industrial Information Systems
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• v.29 no.1
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• pp.77-89
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• 2024

This paper presents an unmanned store management system that can provide inventory management and theft prevention for displayed products using a small camera that can monitor the shelves of sold products in small and medium-sized stores. This system is a service solution that integrates object recognition, real-time communication, security management, access management, and mobile authentication. The proposed system uses a custom YOLOv5-x model to recognize objects on the display, measure quantities in real time, and support real-time data communication with servers through Raspberry Pie. In addition, the number of objects in the database and the object recognition results are compared to detect suspected theft situations and provide burial images at the time of theft. The proposed unmanned store solution is expected to improve the efficiency of small and medium-sized unmanned store operations and contribute to responding to theft.

• 한국HCI학회:학술대회논문집
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• 2006.02a
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• pp.148-153
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• 2006

인간-컴퓨터 상호작용(HCI) 기술은 과거 컴퓨터란 어렵고 소수의 숙련자만이 다루는 것이라는 인식을 바꾸어 놓았다. HCI 는 컴퓨터 사용자인 인간에게 거부감 없이 수용되기 위해 인간과 컴퓨터가 조화를 이루는데 많은 성과를 거두어왔다. 컴퓨터 비전에 기반을 두고 인간과 컴퓨터의 상호작용을 위하여 사용자 의도 및 행위 인식 연구들이 많이 행해져 왔다. 특히 손을 이용한 제스처는 인간과 인간, 인간과 컴퓨터 그리고 최근에 각광받고 있는 인간과 로봇의 상호작용에 중요한 역할을 해오고 있다. 본 논문에서 제안하는 손 추출 및 추적 알고리즘은 비전에 기반한 호출자 인식과 손 추적 알고리즘을 병행한 자연스러운 손 추출 및 추적 알고리즘이다. 인간과 인간 사이의 상호간의 주의집중 방식인 호출 제스처를 인식하여 기반하여 사용자가 인간과 의사소통 하는 것과 마찬가지로 컴퓨터/로봇의 주의집중을 끌도록 하였다. 또한 호출 제스처에 의해서 추출된 손동작을 추적하는 알고리즘을 개발하였다. 호출 제스처는 카메라 앞에 존재할 때 컴퓨터/로봇의 사용자가 자신에게 주의를 끌 수 있는 자연스러운 행동이다. 호출 제스처 인식을 통해 복수의 사람이 존재하는 상황 하에서 또한 원거리에서도 사용자는 자신의 의사를 전달하고자 함을 컴퓨터/로봇에게 알릴 수 있다. 호출 제스처를 이용한 손 추출 방식은 자연스러운 손 추출을 할 수 있도록 한다. 현재까지 알려진 손 추출 방식은 피부색을 이용하고 일정 범위 안에 손이 존재한다는 가정하에 이루어져왔다. 이는 사용자가 제스처를 하기 위해서는 특정 자세로 고정되어 있어야 함을 의미한다. 그러나 호출 제스처를 통해 손을 추출하게 될 경우 서거나 앉거나 심지어 누워있는 상태 등 자연스러운 자세에서 손을 추출할 수 있게 되어 사용자의 불편함을 해소 할 수 있다. 손 추적 알고리즘은 자연스러운 상황에서 획득된 손의 위치 정보를 추적하도록 고안되었다. 제안한 알고리즘은 색깔정보와 모션 정보를 융합하여 손의 위치를 검출한다. 손의 피부색 정보는 신경망으로 다양한 피부색 그룹과 피부색이 아닌 그룹을 학습시켜 얻었다. 손의 모션 정보는 연속 영상에서 프레임간에 일정 수준 이상의 차이를 보이는 영역을 추출하였다. 피부색정보와 모션정보로 융합된 영상에서 블랍 분석을 하고 이를 민쉬프트로 추적하여 손을 추적하였다. 제안된 손 추출 및 추적 방법은 컴퓨터/로봇의 사용자가 인간과 마주하듯 컴퓨터/로봇의 서비스를 받을 수 있도록 하는데 주목적을 두고 있다.

• Journal of Broadcast Engineering
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• v.18 no.3
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• pp.393-400
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• 2013

Hand shape recognition is a fundamental technique for implementing natural human-computer interaction. In this paper, we discuss a method for effectively detecting a hand region in Kinect-based hand shape recognition. Since Kinect is a camera that can capture color images and infrared images (or depth images) together, both images can be exploited for the process of detecting a hand region. That is, a hand region can be detected by finding pixels having skin colors or by finding pixels having a specific depth. Therefore, after analyzing the performance of each, we need a method of properly combining both to clearly extract the silhouette of hand region. This is because the hand shape recognition rate depends on the fineness of detected silhouette. Finally, through comparison of hand shape recognition rates resulted from different hand region detection methods in general environments, we propose a high-performance hand region detection method.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37C no.10
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• pp.925-932
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• 2012

In this paper, we develop a pattern recognition algorithm applied to a humanoid robot which is exploited as a guide for visually handicapped persons to find a desired path to their destinations. Behavior primitives of a humanoid robot are defined, and Canny's edge detection algorithm is employed to extract the pattern and color of the paving blocks that especially devised for visually handicapped persons. Based on these, an efficient path finding algorithm is developed and implemented on a humanoid robot, running on an embedded linux operating system equipped with a video camera. The performance of our algorithm is experimentally examined in terms of the response time and the pattern recognition ratio. In order to validate our algorithm in various realistic environments, the experiments are repeatedly performed by changing the tilt of paving blocks and the brightness in surrounding area. The results show that our algorithm performs sufficiently well to be exploited as a path finding system for visually handicapped persons.

• Convergence Security Journal
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• v.22 no.1
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• pp.29-38
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• 2022

The importance of prevention of epidemics is increasing due to the serious spread of infectious diseases. For prevention of epidemics, we need to focus on the non-contact industry. Therefore, in this paper, a face recognition door lock that controls access through non-contact is designed and developed. First very simple features are combined to find objects and face recognition is performed using Haar-based cascade algorithm. Then the texture of the image is binarized to find features using LBPH. An non-contact door lock system which composed of Raspberry PI 3B+ board, an ultrasonic sensor, a camera module, a motor, etc. are suggested. To verify actual performance and ascertain the impact of light sources, various experiment were conducted. As experimental results, the maximum value of the recognition rate was about 85.7%.

• Broadcasting and Media Magazine
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• v.25 no.1
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• pp.20-27
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• 2020

최근 모바일 기기를 위한 카메라 관련 기술이 발전하면서 취득할 수 있는 영상의 화질 또한 크게 향상되고 있다. 그러나, 일상 생활에서 빈번히 발생하는 다양한 실내외 불규칙한 조명 조건 및 저조도 환경은 여전히 영상 화질 저하를 야기한다. 본 고에서는 이러한 문제를 해결하기 위해 최근 널리 연구되고 있는 심층신경망 기반 영상 화질 개선 연구의 최신 동향을 소개하고자 한다. 먼저, 다양한 최적화 기법을 바탕으로 영상 내 조명 성분을 추정하고, 이를 개선하는 방법들에 대해 간략히 설명한다. 또한, 영상 인식, 객체 검출 등에서 뛰어난 성능을 입증한 합성곱 신경망 구조를 기반으로 영상의 잠재적 특징을 효과적으로 검출한 후 이를 바탕으로 개선된 영상을 생성하는 방법에 대해 설명한다. 다양한 데이터셋에 대한 실험 결과를 통해 인공지능 기반 영상 화질 개선의 우수성을 보인다.