• Proceedings of the KIEE Conference
• /
• 1990.07a
• /
• pp.471-474
• /
• 1990

In this paper, a vision-based inspection algorithm for checking mark quality on an integrated chip(IC) is proposed. In order to reduce the processing time for inspection, we are implemented image arithmetic unit and binary image projection processor in hardware. By adopting the hardwares, the processing time becomes less one sixth of that in case of using software only.

• 제어로봇시스템학회:학술대회논문집
• /
• 2000.10a
• /
• pp.474-474
• /
• 2000

This paper shows that a system with two-link arm can obtain hand reaching movement to a target object projected on a visual sensor by reinforcement learning using a layered neural network. The reinforcement signal, which is an only signal from the environment, is given to the system only when the hand reaches the target object. The neural network computes two joint torques from visual sensory signals, joint angles, and joint angular velocities considering the urn dynamics. It is known that the trajectory of the voluntary movement o( human hand reaching is almost straight, and the hand velocity changes like bell-shape. Although there are some exceptions, the properties of the trajectories obtained by the reinforcement learning are somewhat similar to the experimental result of the human hand reaching movement.

• Journal of the Korea Society of Computer and Information
• /
• v.21 no.2
• /
• pp.17-23
• /
• 2016

NUI is a motion interface. It uses the body of the user without the use of HID device such as a mouse and keyboard to control the device. In this paper, we use a Pi Camera and sensors connected to it with small embedded board Raspberry Pi. We are using the OpenCV algorithms optimized for image recognition and computer vision compared with traditional HID equipment and to implement a more human-friendly and intuitive interface NUI devices. comparison operation detects motion, it proposed a more advanced motion sensors and recognition systems fused connected to the Raspberry Pi.

• Proceedings of the Korean Information Science Society Conference
• /
• 2005.07b
• /
• pp.781-783
• /
• 2005

본 논문은 손 모양 인식을 이용한 비전 기반의 보행 로봇 제어 시스템을 제안한다. 손의 모양을 인식하기 위해서 움직이는 카메라 영상으로부터 정확한 손의 경계선물 추출하고 추적하는 일이 선행되어야 한다. 따라서 본 논문에서는 민 시프트 방법을 사용한 활성 윤곽선 모델 기반의 추적 방법을 제안한다. 제안된 시스템은 손 추출기, 손 추적기, 손 모양 인식기 그리고 로봇 제어기, 4개의 모들로 구성된다. 손 추출기는 영상에서 미리 정의된 손의 모양을 가지는 피부색 영역을 추출한다. 추출된 손의 추적은 활성 윤관선 모델과 민 시프트 방법을 사용하여 실행된다. 그 후 Hue moments를 사용하여 추적된 손의 모양을 인식한다. 제안된 방법을 평가하기 위해서 본 논문에서는 2족 보행 로봇 KHR-1에 제안된 방법을 적용 한다.

• Journal of the Korean Society of Industry Convergence
• /
• v.20 no.2
• /
• pp.89-95
• /
• 2017

In this paper, we suggest the method for a mobile robot to move safely from an initial position to a goal position in the wide environment like a building. There is a problem using odometry encoder sensor to estimate the position of a mobile robot in the wide environment like a building. Because of the phenomenon of wheel's slipping, a encoder sensor has the accumulated error of a sensor measurement as time. Therefore the error must be compensated with using other sensor. A vision sensor is used to compensate the position of a mobile robot as using the regularly attached light's panel on a building's ceiling. The method to create global path planning for a mobile robot model a building's map as a graph data type. Consequently, we can apply floyd's shortest path algorithm to find the path planning. The effectiveness of the method is verified through simulations and experiments.

• International Journal of Computer Science & Network Security
• /
• v.21 no.12
• /
• pp.93-100
• /
• 2021

Satellite communication for high altitude platform stations (HAPS) and geostationary orbit (GEO) systems suffers from sand and dust (SANDU) storms in desert and arid regions. The focus of this paper is to propose common relations between HAPS and GEO for the atmospheric impairments affecting the satellite communication networks operating above Ku-band crossing the propagation path. A double phase three-dimensional relationship for HAPS and GEO systems is then presented. The comparison model present the analysis of atmospheric attenuation with specific focus on sand and dust based on particular size, visibility, adding gas effects for different frequency, and propagation angle to provide systems' operations with a predicted vision of satellite parameters' values. Thus, the proposed system provides wide range of selecting applicable parameters, under different weather conditions, in order to achieve better SNR for satellite communication.

• Proceedings of the KWS Conference
• /
• 2002.10a
• /
• pp.307-313
• /
• 2002

This paper describes a weld pool monitoring technique, which is based on the weld pool image analysis. The proposed image analysis algorithm uses machine vision techniques to extract geometrical information from the weld pool image such as maximum weld pool width, gap width and misalignment between the joint longitudinal axis and the welding wire. These can be related to the welding parameters (welding voltage and current, wire feed speed and standoff) to produce control actions necessary to ensure that the required weld quality will be achieved. The experiments have shown that the algorithm is able to produce good estimates of the weld pool geometry; however, the adjustment of the camera parameters affects the image quality and, consequently, has a great influence over the estimation.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2007.11a
• /
• pp.197-200
• /
• 2007

본 논문에서는 로봇 컨트롤 시스템을 위해 입력 받은 영상부터 몇 가지의 손 제스처를 인식하는 비전기반 손 제스처 인식방법을 제안한다. 로봇으로부터 입력 받은 이미지는 로봇의 위치, 주변환경, 조명 등 여러 요인에 따라 다양하게 존재한다. 본 논문은 다양한 환경에서 입력되는 영상으로부터 시스템이 로봇 컨트롤을 위해 미리 지정한 몇 가지 제스처를 인식하도록 한다. 먼저 이미지 조명 변화에 강한 손 제스처 인식을 위하여 레티넥스 이미지 정규화를 적용한 후, YCrCb 공간 상에서 입력된 영상에서 손 영역을 검출 후 위치를 추정한다. 인식된 손 영역에서 특징벡터를 추출함으로서 입력 영상내의 존재할 수 있는 손의 크기나 손의 회전각도 등에 상관없이 필요로 하는 제스처를 인식하도록 한다. 제안된 제스처 인식 결과는 로봇컨트롤을 위한 기존의 제스처인식과 비교하여 성능을 측정하였다.

• Journal of the Institute of Electronics Engineers of Korea SC
• /
• v.45 no.6
• /
• pp.55-59
• /
• 2008

For effective mobility control of UGV(unmanned ground vehicle), the terrain cover classification is an important component as well as terrain geometry recognition and obstacle detection. The vision based terrain cover classification algorithm consists of pre-processing, feature extraction, classification and post-processing. In this paper, we present a method to classify terrain covers based on the color and texture information. The color space conversion is performed for the pre-processing, the wavelet transform is applied for feature extraction, and the SVM(support vector machine) is applied for the classifier. Experimental results show that the proposed algorithm has a promising classification performance.

• Journal of Electrical Engineering and Technology
• /
• v.10 no.6
• /
• pp.2384-2392
• /
• 2015

The technical development and practical applications of big-data for health is one hot topic under the banner of big-data. Big-data medical image fusion is one of key problems. A new fusion approach with coding based on Spherical Coordinate Domain (SCD) in Wireless Sensor Network (WSN) for big-data medical image is proposed in this paper. In this approach, the three high-frequency coefficients in wavelet domain of medical image are pre-processed. This pre-processing strategy can reduce the redundant ratio of big-data medical image. Firstly, the high-frequency coefficients are transformed to the spherical coordinate domain to reduce the correlation in the same scale. Then, a multi-scale model product (MSMP) is used to control the shrinkage function so as to make the small wavelet coefficients and some noise removed. The high-frequency parts in spherical coordinate domain are coded by improved SPIHT algorithm. Finally, based on the multi-scale edge of medical image, it can be fused and reconstructed. Experimental results indicate the novel approach is effective and very useful for transmission of big-data medical image(especially, in the wireless environment).