• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.3
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• pp.160-173
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• 2013

In this paper, we propose a new visual odometry technique by combining a forward-looking stereo camera and a backward-looking monocular camera. The main goal of the proposed technique is to identify the location of a moving vehicle which travels long distance and comes back to the initial position in urban road environments. While the vehicle is moving to the destination, a global 3D map is updated continuously by a stereo visual odometry technique using a graph theorem. Once the vehicle reaches the destination and begins to come back to the initial position, a map-based monocular visual odometry technqieu is used. To estimate the position of the returning vehicle accurately, 2D features in the backward-looking camera image and the global map are matched. In addition, we utilize the previous matching nodes to limit the search ranges of the next vehicle position in the global map. Through two navigation paths, we analyze the accuracy of the proposed method.

• Proceedings of the IEEK Conference
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• 2008.06a
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• pp.775-776
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• 2008

본 논문은 WLAN 환경에서 웨이블릿과 신경망을 사용한 실내 위치인식 방법을 제안한다. 제안한 방법의 기본적인 아이디어는 경제적이면서 효율적인 방법으로써 실내에 설치된 무선 AP들로부터 수신된 신호들의 수신세기로부터 비교적 정확하게 위치를 추정하는 연구이다. 일반적으로 무선 신호는 주위 환경 및 건물 구조적 요인에 의해 수신세기가 더해지거나 감해지는 현상이 발생함으로써 수신된 각 신호세기로부터 신호 잡음과 오류에 강인하고 시간과 주파수 도메인의 정보 표현이 가능하며 각 신호세기들간의 구별성을 갖는 특징값 획득이 필요하다. 제안 방법에서는 웨이블릿 변환을 이용하여 수신된 신호로부터 중복 데이터와 잡음에 민감하게 반응하지 않는 특징값을 획득하고, 수신신호 전역 및 지역적 특징의 표현이 가능한 신경망을 사용하여 실내위치인식 방법은 제안한다. 실험 결과 실내위치 인식률이 94 % 이상 제시하였다.

• Journal of KIISE:Software and Applications
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• v.32 no.8
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• pp.759-768
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• 2005

This paper describes an algorithm that can recognize gestures constructing subspace gesture symbols with hybrid feature information. The previous popular methods based on geometric feature and appearance have resulted in ambiguous output in case of recognizing between similar gesture because they use just the Position information of the hands, feet or bodily shape features. However, our proposed method can classify not only recognition of motion but also similar gestures by the partial feature information presenting which parts of body move and the global feature information including 2-dimensional bodily motion. And this method which is a simple and robust recognition algorithm can be applied in various application such surveillance system and intelligent interface systems.

• The KIPS Transactions:PartD
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• v.12D no.3 s.99
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• pp.481-492
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• 2005

To guide the guiding robot for the visually impaired carefully, the digital map to be used to search a path must be detailed and has some information about dangerous spots. It also has to search not only safe but also short path through the position data by GPS and INS sensors. In this paper, as the difference of the ability that the visually unpaired can recognize, we have developed the localization tracking system so that it can make a movement path and verify position information, and the global navigation system for the visually impaired using the GPS and INS. This system can be used when the visually impaired move short path relatively. We had also verified that the system was able to correct the position as the assistant navigation system of the GPS on the outside.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.45 no.5
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• pp.38-47
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• 2008

The most commonly used location recognition system is the GPS-based approach. However, the GPS is inefficient for an indoor or urban area where high buildings shield the satellite signals. To overcome this problem, this paper propose the indoor positioning method using wavelet and neural network. The basic idea of proposed method is estimated the location using the received signal strength from wireless APs installed in the indoor environment. Because of the received signal strength of wireless radio signal is fluctuated by the environment factors, a feature that is strength of signal noise and error and express the time and frequency domain is need. Therefore, this paper is used the wavelet coefficient as the feature. And the neural network is used for estimate the location. The experiment results indicate 94.6% an location recognition rate.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.31 no.4
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• pp.517-524
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• 2007

This paper presents a global localization method using circular correlation of an omni-directional image. The localization of a mobile robot, especially in indoor conditions, is a key component in the development of useful service robots. Though stereo vision is widely used for localization, its performance is limited due to computational complexity and its narrow view angle. To compensate for these shortcomings, we utilize a single omni-directional camera which can capture instantaneous $360^{\circ}$ panoramic images around a robot. Nodes around a robot are extracted by the correlation coefficients of CHL (Circular Horizontal Line) between the landmark and the current captured image. After finding possible near nodes, the robot moves to the nearest node based on the correlation values and the positions of these nodes. To accelerate computation, correlation values are calculated based on Fast Fourier Transforms. Experimental results and performance in a real home environment have shown the feasibility of the method.

• Proceedings of the Korea Information Processing Society Conference
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• 2015.10a
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• pp.1358-1360
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• 2015

본 논문에서는 MB-LBP(Multi-scale Block Local Binary Patterns)와 공간피라미드를 이용하여 생성된 특징을 랜덤 포레스트(Random Forest) 분류기에 적용하여 영상내의 표지판 속도를 인식하는 알고리즘을 제안한다. 입력 영상에서 표지판 영역은 다양한 위치와 크기를 가지며 주위 배경이 후보 영역에 포함되므로 먼저 입력 영상에 원형 Hough Transform을 적용하여 원형의 표지판 후보 영역만을 검출한다. 그 후 영상의 화질을 향상시키기 위해 히스토그램 평활화와 모폴로지 연산을 적용하여 표지판의 숫자 영역과 배경 영역의 대비를 높이도록 한다. 표지판의 크기 변화에 강건한 시스템의 구현을 위해 후보 영역에서 LBP(Local Binary Patterns)보다 우수한 성능을 보이는 MB-LBP를 적용하고, 다양한 크기의 속도 표지판을 인식하기 위해 공간 피라미드를 사용하여 지역적 특징과 전역적 특징 모두를 추출하였다. 추출된 특징은 랜덤 포레스트(Random Forest)를 이용하여 각 9개의 속도 표지판으로 분류, 각 속도별 클래스에 대한 인식 성능을 측정하였다.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.6C
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• pp.801-814
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• 2004

In this paper, we propose a block adaptive binarization (BAB) using a modified quadratic filter (MQF) to binarize business card images acquired by personal digital assistant (PDA) cameras effectively. In the proposed method, a business card image is first partitioned into blocks of 8${\times}$8 and the blocks are then classified into character Hocks (CBs) and background blocks (BBs). Each classified CB is windowed with a 24${\times}$24 rectangular window centering around the CB and the windowed blocks are improved by the pre-processing filter MQF, in which the scheme of threshold selection in QF is modified. The 8${\times}$8 center block of the improved block is barbarized with the threshold selected in the MQF. A binary image is obtained tiling each binarized block in its original position. Experimental results show that the MQF and the BAB have much better effects on the performance of binarization compared to the QF and the global binarization (GB), respectively, for the test business card images acquired in a PDA. Also the proposed BAB using MQF gives binary images of much better quality, in which the characters appear much better clearly, over the conventional GB using QF. In addition, the binary images by the proposed BAB using MQF yields about 87.7% of character recognition rate so that about 32.0% performance improvement over those by the GB using QF yielding about 55.7% of character recognition rate using a commercial character recognition software.

• Journal of the Korea Society of Computer and Information
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• v.15 no.12
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• pp.181-188
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• 2010

This paper proposes 3D visualization systems for the real-time situation awareness and a state information of the aircraft. This system was embodied with OpenGL and the Google Earth of web base using situation data of the aircraft. The existing system has problem which speed decrease and visible restricted map because massive data of terrain and satellite photo. This system is supports the visualization tool which is economic and entire area for a real-time situation awareness with minimum flight information using Open-API of the Google Earth. Also provides a visible convenience to expansion-view using multiple location information. This research result could be used to system for the situation awareness of the aircraft from web environment.

• Electronics and Telecommunications Trends
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• v.36 no.2
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• pp.22-31
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• 2021

This report introduces a definition for robot task intelligence and explains the basis of the challenges associated with implementing robot task intelligence in real-world problems. Two fundamental elements of this intelligence, robot manipulation and navigation, are introduced herein. We describe the existing trends and industrial applications of the robot task intelligence in logistics and agricultural automation. Furthermore, as an underpinning technology for this intelligence, we review the existing three-dimensional position estimation techniques and summarize the difficulties associated with applying pure SLAM technology to real-world applications. Finally, we discuss the prospects of the robot task intelligence research and its potential for solving real-world problems.