In this paper, we present a case study of developing MVIS (Machine Vision Inspection System) designed for exterior quality inspection of stamping dies used in the production of automotive exterior components in a small to medium-sized factory. While the primary processes within the factory, including machining, transportation, and loading, have been automated using PLCs, CNC machines, and robots, the final quality inspection process still relies on manual labor. We implement the MVIS with general- purpose industrial cameras and Python-based open-source libraries and frameworks for rapid and low-cost development. The MVIS can play a major role on improving throughput and lead time of stamping dies. Furthermore, the processed inspection images can be leveraged for future process monitoring and improvement by applying deep learning techniques.

The purpose of this study is to design and develop integrated game system for experiential walking exercise. Existing walking exercise is performed outside, so it is influenced by external weather, temperature, time, place and other situation information. Therefore, it is necessary to have an experiential walking exercise game that can induce the recommended level of physical activity for the elderly who have a low interest in health care. The experiential exercise game requires a vision - based system to recognize motion and a smart mat that can recognize walking information. We also developed a walking exercise program to improve the sense of balance and cognitive ability of elderly people. There are 4 types of Walking Exercise Games: 5 levels for beginner, intermediate, and advanced difficulty levels.

This study proposes automation measures of anti-collision detection within EMS(Electrical Mono Rail System). EMS is a full automation transport equipment mainly used in production process, such as car manufacturing planets, electronic factories and food processing plants among manufactures. This research paper presents a plan for creating a smart EMS and overcoming an weakness of EMS. The mechanical strength and durability are ensured in the expected major collision region by performing a CAE analysis. Automated equipment has to respond to a sudden accident which is based on the self-image recording function and wireless transmission function. This equipment will record a sudden crash course in real time and record it. This record eventually becomes known to distant places with users. Because of this equipment, the unexpected accident is prevented and is reduced a human damage and is expected to improve productivity. Therefore, this research results are as follows. The first, the full automated conveyor controller is developed within from 3 to 4 millimeter stop range according to increase of load weight in 1.5 tons. The second, wireless image recording system for the measures of unexpected accident is developed through the CAE analysis of main parts for the exact stop control. The most important final purpose of this research is developed the wireless image recording system for the unexpected accident.

Recently, the automotive part manufacturers have made a lot of efforts to increase the reliability of their products for various reasons. For that reason, many manufacturers have tried to get the automatic inspection system for their products. The automatic system can reduce the number of the workers and increase the accuracy of the inspection. In this study, inspection subject is brake-hose resonator. This component is made through a high frequency bonding process and can have the possibility of a defect like a leak problem. The purpose of this study is to make the automatic inspection system for detecting the implied leak problem of the products with the vision system. Consequently, this study show that the vision system is a very reasonable method to detect the leak problem. The automatic inspection system can decrease the detection time from 35s/EA to 22s/EA in case of continuous operation.

철도교의 장기변위 정보는 시공 및 유지관리에 있어 매우 유용하지만, 실구조물의 장기간에 걸쳐 발생하는 변위를 정확하게 계측하기 위해서는 많은 실질적인 문제를 해결해야 한다. 본 연구에서는 철도교량의 효과적인 장기변위 계측을 위해, 컴퓨터 비전 기반의 비접촉식 기법을 제안한다. 컴퓨터 비전 기반 기법은 비용적인 측면에서 우수하며 사용이 간편하여 최근 교량변위 계측을 위해 기술개발이 활발하게 되고 있으나, 카메라의 미소변위에 의해 큰 오차가 발생하므로, 장기변위의 계측에는 적합하지 않다. 본 연구에서는 두 개의 카메라를 이용하여 카메라 변위에 따른 오차를 보정하는 방식으로 장기변위 계측을 가능하게 하였다. 개발된 기법을 시공 중인 철도교량에 적용하여 성능을 검증하였다.

In this paper, we propose an algorithm that estimates the location of lunar rover using IMU and vision system instead of the dead-reckoning method using IMU and encoder, which is difficult to estimate the exact distance due to the accumulated error and slip. First, in the lunar environment, magnetic fields are not uniform, unlike the Earth, so only acceleration and gyro sensor data were used for the localization. These data were applied to extended kalman filter to estimate Roll, Pitch, Yaw Euler angles of the exploration rover. Also, the lunar module has special color which can not be seen in the lunar environment. Therefore, the lunar module were correctly recognized by applying the HSV color filter to the stereo image taken by lunar rover. Then, the distance between the exploration rover and the lunar module was estimated through SIFT feature point matching algorithm and geometry. Finally, the estimated Euler angles and distances were used to estimate the current position of the rover from the lunar module. The performance of the proposed algorithm was been compared to the conventional algorithm to show the superiority of the proposed algorithm.

Computer vision-based displacement measurement is regarded as an excellent alternative to conventional displacement measurement devices due to its convenient installation process with high accuracy. Based on the strong potential, this study proposes a computer vision approach for displacement measurement with enhanced field applicability. Main features of the proposed method are (1) robustness against adverse light conditions and (2) convenient camera installation that allows the camera to be arbitrarily placed. An adaptive image processing procedure is developed to overcome false identification of target markers that can be induced by strong lights. Location information of the identified markers are used to obtain displacement using the homography transformation, which allows the camera to be installed in any place as long as the target markers are in the line of sight. With these features, the computer vision approach is experimentally proven to be practical in field testing for measuring structural displacement.

SHM에서 변위는 구조물의 동적 특성을 파악하는 핵심정보다. 이를 구조물과 직접 접촉하여 자기장 변화를 전기적신호(LVDT), 직접적으로 측정하는 방안으로 LVDT, GPS, LDV Displacement is one of the most fundamental responses, containing useful information regarding dynamic behavior of a structure. Traditional displacement measurement devices such as LVDT have disadvantages in its high-cost and few options on installation place. For the sake of economic reason, vision-based displacement measurement systems using low-cost cameras have been developed, yet these approaches still have difficulties in finding appropriate camera positions; camera should be placed perpendicular to targets. This study presents a new vision-based displacement measurement system using the planar homography method that gives accurate displacement, allowing the camera to have an arbitrary angle toward target. The vision-based system is experimentally verified using a low-cost camera and a target with four circles.

This paper studies how to combine devices such as monocular/stereo cameras, motors for panning/tilting, fisheye lens and convex mirrors, in order to solve vision-based robotic problems. To overcome the well-known trade-offs between optical properties, we present two mixed versions of the new systems. The first system is the robot photographer with a conventional pan/tilt perspective camera and fisheye lens. The second system is the omnidirectional detector for a complete 360-degree field-of-view surveillance system. We build an original device that combines a stereo-catadioptric camera and a pan/tilt stereo-perspective camera, and also apply it in the real environment. Compared to the previous systems, we show benefits of two proposed systems in aspects of maintaining both high-speed and high resolution with collaborative moving cameras and having enormous search space with hybrid configuration. The experimental results are provided to show the effectiveness of the mixing collaborative and hybrid systems.

This paper presents a localization system using ceiling images in a large indoor environment. For a system with low cost and complexity, we propose a single camera based system that utilizes ceiling images acquired from a camera installed to point upwards. For reliable operation, we propose a method using hybrid features which include natural landmarks in a natural scene and artificial landmarks observable in an infrared ray domain. Compared with previous works utilizing only infrared based features, our method reduces the required number of artificial features as we exploit both natural and artificial features. In addition, compared with previous works using only natural scene, our method has an advantage in the convergence speed and robustness as an observation of an artificial feature provides a crucial clue for robot pose estimation. In an experiment with challenging situations in a real environment, our method was performed impressively in terms of the robustness and accuracy. To our knowledge, our method is the first ceiling vision based localization method using features from both visible and infrared rays domains. Our system can be easily utilized with a variety of service robot applications in a large indoor environment.

In this paper, we describe an image processing algorithm which is able to recognize the road lane. This algorithm performs to recognize the interrelation between AGV and the other vehicle. We experimented on AGV driving test with color CCD camera which is setup on the top of vehicle and acquires the digital signal. This paper is composed of two parts. One is image preprocessing part to measure the condition of the condition of the lane and vehicle. This finds the information of lines using RGB ratio cutting algorithm, the edge detection and Hough transform. The other obtains the situation of other vehicles using the image processing and viewport. At first, 2 dimension image information derived from vision sensor is interpreted to the 3 dimension information by the angle and position of the CCD camera. Through these processes, if vehicle knows the driving conditions which are lane angle, distance error and real position of other vehicles, we should calculate the reference steering angle.