• Title/Summary/Keyword: Computer vision technology

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Multi-lane Road Recognition Model Applying Computer Vision (컴퓨터비전을 적용한 다차선 도로 인식 모델)

  • Kim, Do-Young;Jang, Jong-Wook;Jang, Sung-Jin
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2021.10a
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    • pp.317-319
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    • 2021
  • In Korea, an intelligent transportation system(ITS) is established to efficiently operate traffic congestion on roads and is being used for traffic information collection and speed control systems. Currently, designated and dedicated lanes are in place to ensure traffic circulation and traffic safety, and systematic and accurate illegal vehicle crackdown systems with artificial intelligence technology are needed. In this study, we propose a vehicle number recognition model that can improve the efficiency of the traffic of designated vehicles. By applying computer vision technology, we are going to identify three-lane and four-lane multi-lane roads in real time and detect vehicle numbers by car to suggest ways to crack down on vehicles that violate the designated lane system.

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Vision-based Navigation for VTOL Unmanned Aerial Vehicle Landing (수직이착륙 무인항공기 자동 착륙을 위한 영상기반 항법)

  • Lee, Sang-Hoon;Song, Jin-Mo;Bae, Jong-Sue
    • Journal of the Korea Institute of Military Science and Technology
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    • v.18 no.3
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    • pp.226-233
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    • 2015
  • Pose estimation is an important operation for many vision tasks. This paper presents a method of estimating the camera pose, using a known landmark for the purpose of autonomous vertical takeoff and landing(VTOL) unmanned aerial vehicle(UAV) landing. The proposed method uses a distinctive methodology to solve the pose estimation problem. We propose to combine extrinsic parameters from known and unknown 3-D(three-dimensional) feature points, and inertial estimation of camera 6-DOF(Degree Of Freedom) into one linear inhomogeneous equation. This allows us to use singular value decomposition(SVD) to neatly solve the given optimization problem. We present experimental results that demonstrate the ability of the proposed method to estimate camera 6DOF with the ease of implementation.

Edge-based Method for Human Detection in an Image (영상 내 사람의 검출을 위한 에지 기반 방법)

  • Do, Yongtae;Ban, Jonghee
    • Journal of Sensor Science and Technology
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    • v.25 no.4
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    • pp.285-290
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    • 2016
  • Human sensing is an important but challenging technology. Unlike other methods for sensing humans, a vision sensor has many advantages, and there has been active research in automatic human detection in camera images. The combination of Histogram of Oriented Gradients (HOG) and Support Vector Machine (SVM) is currently one of the most successful methods in vision-based human detection. However, extracting HOG features from an image is computer intensive, and it is thus hard to employ the HOG method in real-time processing applications. This paper describes an efficient solution to this speed problem of the HOG method. Our method obtains edge information of an image and finds candidate regions where humans very likely exist based on the distribution pattern of the detected edge points. The HOG features are then extracted only from the candidate image regions. Since complex HOG processing is adaptively done by the guidance of the simpler edge detection step, human detection can be performed quickly. Experimental results show that the proposed method is effective in various images.

Ball Grid Array Solder Void Inspection Using Mask R-CNN

  • Kim, Seung Cheol;Jeon, Ho Jeong;Hong, Sang Jeen
    • Journal of the Semiconductor & Display Technology
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    • v.20 no.2
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    • pp.126-130
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    • 2021
  • The ball grid array is one of the packaging methods that used in high density printed circuit board. Solder void defects caused by voids in the solder ball during the BGA process do not directly affect the reliability of the product, but it may accelerate the aging of the device on the PCB layer or interface surface depending on its size or location. Void inspection is important because it is related in yields with products. The most important process in the optical inspection of solder void is the segmentation process of solder and void. However, there are several segmentation algorithms for the vision inspection, it is impossible to inspect all of images ideally. When X-Ray images with poor contrast and high level of noise become difficult to perform image processing for vision inspection in terms of software programming. This paper suggests the solution to deal with the suggested problem by means of using Mask R-CNN instead of digital image processing algorithm. Mask R-CNN model can be trained with images pre-processed to increase contrast or alleviate noises. With this process, it provides more efficient system about complex object segmentation than conventional system.

Field System based on Embedded Linux for Music Mood Lighting (음악감성 조명기용 임베디드 리눅스 기반 필드 시스템)

  • Kim, Hyun-Soo;Moon, Chang-Bae;Yi, Jong-Yeol;Kim, Byeong-Man
    • Proceedings of the Korea Multimedia Society Conference
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    • 2012.05a
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    • pp.211-214
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    • 2012
  • 스트레스는 다양한 질병의 원인이 되며 스트레스의 해소는 질병 예방에 중요한 요인이라 할 수 있을 것이다. 스트레스를 해소시키는 방법 중 한 가지는 청각이나 시각을 이용하는 방법이다. 청각과 시각을 동시에 이용할 수 있다면 그 효과를 극대화 할 수 있을 것이다. 본 논문에서는 음악의 분위기를 자동으로 파악하고, 파악한 음악의 분위기를 표현할 수 있는 음악감성 조명기용 임베디드 리눅스 기반 필드 시스템을 제안하였다. 본 논문에서 제시한 필드서버를 감성조명과 함께 공원이나 가정집 등에 제공할 수 있을 것이고, 음악과 조명을 동시에 제공함으로 현대인 질병의 원인이라 할 수 있는 스트레스 해소가 가능할 것이다. 또한 본 논문의 시스템을 이용하여 임상실험을 실시하여 임상데이터를 확보한다면 심리 치료를 목적으로 하는 의학적 도구로 발전 할 수 있을 것으로 보인다.

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A Machine Vision System for Inspection of Car Sunroof Using SVM Algorithm (SVM 학습 알고리즘을 이용한 자동차 썬루프 장치의 볼트 유무 검사 장비)

  • Kim, Giseok;Lee, Saac;Cho, Jae-Soo
    • Proceedings of the Korea Information Processing Society Conference
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    • 2013.05a
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    • pp.289-292
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    • 2013
  • 본 논문은 SVM(Support Vector Machine) 학습알고리즘을 이용하여 자동차 썬루프 장치의 볼트 유무를 검사하는 자동차 부품 검사 장비에 관한 것이다. 자동화 시스템은 높은 정밀도와 생산성을 위한 빠른 처리 속도를 요구한다. 이를 위해 본 논문에서는 선형 SVM 학습알고리즘을 활용하여 자동차 썬루프 장치의 볼트 유무를 검사하는 알고리즘을 개발하였다. SVM 알고리즘은 분류를 위한 알고리즘이지만 ROI(Region-Of-Interest) 내의 모든 윈도우에 대한 분류를 수행하여 검출기 역할을 할 수 있도록 한다. 볼트가 있는 경우와 볼트가 없는 경우가 아닌 네거티브 샘플을 확보하기 위해 검출 대상 물체 주변에서 다양한 네거티브 샘플들을 추출한다. 그 결과 물체가 예상 위치에서 다소 빗나가는 경우에도 볼트 유무를 판별할 수 있을 뿐 아니라 볼트의 위치까지 검출할 수 있고, 처리 속도에서 자동화 시스템이 요구하는 수준에 도달함을 실험 결과를 통해 검증한다.

Vision-Based Robust Control of Robot Manipulators with Jacobian Uncertainty (자코비안 불확실성을 포함하는 로봇 매니퓰레이터의 영상기반 강인제어)

  • Kim, Chin-Su;Jie, Min-Seok;Lee, Kang-Woong
    • Journal of Advanced Navigation Technology
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    • v.10 no.2
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    • pp.113-120
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    • 2006
  • In this paper, a vision-based robust controller for tracking the desired trajectory a robot manipulator is proposed. The trajectory is generated to move the feature point into the desired position which the robot follows to reach to the desired position. To compensate the parametric uncertainties of the robot manipulator which contain in the control input, the robust controller is proposed. In addition, if there are uncertainties in the Jacobian, to compensate it, a vision-based robust controller which has control input is proposed as well in this paper. The stability of the closed-loop system is shown by Lyapunov method. The performance of the proposed method is demonstrated by simulations and experiments on a two degree of freedom 5-link robot manipulators.

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Development of a Lateral Control System for Autonomous Vehicles Using Data Fusion of Vision and IMU Sensors with Field Tests (비전 및 IMU 센서의 정보융합을 이용한 자율주행 자동차의 횡방향 제어시스템 개발 및 실차 실험)

  • Park, Eun Seong;Yu, Chang Ho;Choi, Jae Weon
    • Journal of Institute of Control, Robotics and Systems
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    • v.21 no.3
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    • pp.179-186
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    • 2015
  • In this paper, a novel lateral control system is proposed for the purpose of improving lane keeping performance which is independent from GPS signals. Lane keeping is a key function for the realization of unmanned driving systems. In order to obtain this objective, a vision sensor based real-time lane detection scheme is developed. Furthermore, we employ a data fusion along with a real-time steering angle of the test vehicle to improve its lane keeping performance. The fused direction data can be obtained by an IMU sensor and vision sensor. The performance of the proposed system was verified by computer simulations along with field tests using MOHAVE, a commercial vehicle from Kia Motors of Korea.

Development of an Algorithm for the Vision-Based Surface-Strain Measurment of Large Stamped Parts (비전을 이용한 중.대형 판재성형 제품의 곡면 변형률 측정 알고리듬 개발)

  • 김형종
    • Proceedings of the Korean Society for Technology of Plasticity Conference
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    • 1999.03b
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    • pp.269-272
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    • 1999
  • It is still hard to measure the strain distribution over entire surface of a medium or large-size stamped part even by using an automated strain measurement system. Several methods which enable to enlarge the measurement range without losing accuracy and precision are suggested in this study, The superposition of images having different high-lightened or damaged part each other results in an enhanced image. A new method for constructing the element connectivity from a line-thinned image makes it possible to identify up to 1,000 elements. And the geometry assembling algorithm is proved very efficient in which the whole area to be measured is divided into several parts ; the coordinate transformation between every two adjacent parts is obtained from the concept of the least square error ; and the 3-D shape or strain distribution over the whole surface is assembled,

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A New Robotic 3D Inspection System of Automotive Screw Hole

  • Baeg, Moon-Hong;Baeg, Seung-Ho;Moon, Chan-Woo;Jeong, Gu-Min;Ahn, Hyun-Sik;Kim, Do-Hyun
    • International Journal of Control, Automation, and Systems
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    • v.6 no.5
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    • pp.740-745
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    • 2008
  • This paper presents a new non-contact 3D robotic inspection system to measure the precise positions of screw and punch holes on a car body frame. The newly developed sensor consists of a CCD camera, two laser line generators and LED light. This lightweight sensor can be mounted on an industrial robot hand. An inspection algorithm and system that work with this sensor is presented. In performance evaluation tests, the measurement accuracy of this inspection system was about 200 ${\mu}m$, which is a sufficient accuracy in the automotive industry.