• Journal of Institute of Control, Robotics and Systems
• /
• v.6 no.2
• /
• pp.164-172
• /
• 2000

To follow a moving target keeping a certain distance it is essential for a mobile robot to detect the target first and to measure its pose and velocity. This paper proposes a new solution for this problem using the accumulated ultrasonic image which is constructed by accumulating the returned ultrasonic signal along the time axis for a certain number of measurement periods. A moving target is separated by selecting the trajectory whose inclination is different from others in the imag since the inclination of a trajectory represents the relative speed of the target against the mobile robot. The proposed algorithm was implemented on a mobile robot and has shown that the robot follows a moving target successfully.

• Journal of Welding and Joining
• /
• v.22 no.6
• /
• pp.43-49
• /
• 2004

In this study, a visual sensor system which can detect I-butt weld joint with height variation and includes a seam tracking algorithm was investigated. Three-dimensional position of an object can be acquired by using the method of distance measurement, i.e., an optical trigonometry which results from the spatial relations between the camera, the object and the structured light by a visible laser. Effects of laser intensity and iris number for the image quality as well as object material were investigated for the optical system design. For the image processing, a region of interest is defined from the whole image and a line image of laser is drew by using the gray level difference in the image. From the drew laser line, the weld joint can be recognized in searching the biggest point position calculated from the central difference method. Through a series of welding experiments, a good tracking performance was confirmed under GMA welding.

• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 2001.04a
• /
• pp.125-130
• /
• 2001

Skilled typists can type characters or words without looking at keyboard, relying on the finger's relative position. If the relative positions of the fingers can be identified, a virtual keyboard may be accomplished by applying the concept of "DataGlove" or "FingerRing". The virtual keyboard may be efficient as a new mobile input device supporting QWERTY keyboard layout. For the purpose of investigating skilled typing pattern, in this paper the touch-positions of the fingers are measured with a touchscreen while five skilled typists type a long sentence. From these measurements it can be observed that the groups of touch-positions are classified into alphabet characters. Though there are some overlapped groups we can find constant distances capable of being discriminated among the groups from investigation of the change of touch-position for touch-time. Based on the analysis, the prediction algorithm of the constant distance is proposed and evaluated, which is useful for realization of a portable virtual keyboard.le virtual keyboard.

• Journal of Institute of Control, Robotics and Systems
• /
• v.16 no.8
• /
• pp.751-755
• /
• 2010

In this paper, we proposed an omnidirectional ranging system that is able to obtain $360^{\circ}$ all directional distances effectively based on structured light image. The omnidirectional ranging system consists of laser structured light source and a catadioptric omnidirectional camera with a curved mirror. The proposed integro-differential structured light image processing algorithm makes the ranging system robust against environmental illumination condition. The omnidirectional ranging system is useful for map-building and self-localization of a mobile robot.

• Proceedings of the IEEK Conference
• /
• 2003.07e
• /
• pp.2020-2023
• /
• 2003

In this paper, our proposed system uses the regional Gabor wavelet and Neural Network to implement face recognition similar to human face recognition system, because the Gator wavelet expresses visual recognition system of human mathematically and the regional Neural Network is robust to white noise and partial illumination. This system consists of two stages of building database and recognizing face. One is composed by using the supervised learning of Neural Network. At this time, the Neural Network is applied to the upper and the lower part of face images respectively. The Backpropagation algorithm is used to learn Neural Network. Another consists of calibration of slope of face image, measurement of illumination variant using deviation with average face image and similarity comparison using Euclidean distance measure.

• Journal of information and communication convergence engineering
• /
• v.14 no.4
• /
• pp.215-221
• /
• 2016

We consider a design of a combined quantizer and estimator for distributed systems wherein each node quantizes its measurement without any communication among the nodes and transmits it to a fusion node for estimation. Noting that the quantization partitions minimizing the estimation error are not independently encoded at nodes, we focus on the parameter regions created by the partitions and propose a cluster-based quantization algorithm that iteratively finds a given number of clusters of parameter regions with each region being closer to the corresponding codeword than to the other codewords. We introduce a new metric to determine the distance between codewords and parameter regions. We also discuss that the fusion node can perform an efficient estimation by finding the intersection of the clusters sent from the nodes. We demonstrate through experiments that the proposed design achieves a significant performance gain with a low complexity as compared to the previous designs.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2005.05a
• /
• pp.785-788
• /
• 2005

일정한 형태의 물체를 분석하기 위해 사용되는 각-거리 그래프를 이용하여 임의의 물체의 경계선 내부 영역의 면적을 측정하는 영상처리 알고리듬을 제안한다. 물체의 경계선 내부의 한 점을 중심으로 1차 각-거리 그래프를 생성하고 이 그래프로부터 거리 값이 급격히 변화하는 위치를 추출하여 1 차 그래프에서 접근하지 못한 영역을 인식하여 새 영역에서의 한 점을 중심으로 2 차 각-거리 그래프를 생성한다. 이와 같이 계층적으로 구성된 각-거리 그래프 그룹에 대해 거리의 제곱을 각도 방향으로 적분하여 물체의 경계선 내부 영역의 면적을 측정한다.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.13 no.10
• /
• pp.5197-5218
• /
• 2019

Large-scale retrieval algorithm is problem for visual analyses applications, along its research track. In this paper, we propose a high-efficiency region division-based image retrieve approaches, which fuse low-level local color histogram feature and texture feature. A novel image region division is proposed to roughly mimic the location distribution of image color and deal with the color histogram failing to describe spatial information. Furthermore, for optimizing our region division retrieval method, an image descriptor combining local color histogram and Gabor texture features with reduced feature dimensions are developed. Moreover, we propose an extended Canberra distance method for images similarity measure to increase the fault-tolerant ability of the whole large-scale image retrieval. Extensive experimental results on several benchmark image retrieval databases validate the superiority of the proposed approaches over many recently proposed color-histogram-based and texture-feature-based algorithms.

• Journal of electromagnetic engineering and science
• /
• v.10 no.4
• /
• pp.250-255
• /
• 2010

This paper presents a non-contact measurement method of vital signal by the use of multiple-input multiple-output (MIMO) bio-radar system, configured with two antennas that are separated by a certain distance. The direction of arrival (DOA) estimation algorithm for coherent sources was applied to detect vital signals coming from different spatial angles. The proposed MIMO bio-radar system was composed of two identical transceivers sharing single VCO with a PLL. In order to verify the performance of the system, the DOA estimation experiment was completed with respect to the human target at angles varying between $-50^{\circ}$ and $50^{\circ}$ where the bio-radar system was placed at distances (corresponding to 50 cm and 95 cm) in front of a human target. The proposed MIMO bio-radar system can successfully find the direction of a human target.

• Journal of Navigation and Port Research
• /
• v.31 no.7
• /
• pp.563-568
• /
• 2007

In this paper, an adaptive neural network controller and its application to automatic berthing control of ship is presented. The neural network controller is trained online using adaptive interaction technique without any teaching data and off-line training phase. Firstly, the neural networks used to control rudder and propeller during automatic berthing process are presented. Secondly, computer simulations of automatic ship berthing are carried out in Pusan bay to verify the proposed controller under the influence of wind disturbance and measurement noise. The results of simulation show good performance of the developed berthing control system.