• The Journal of Korea Robotics Society
• /
• v.18 no.1
• /
• pp.66-71
• /
• 2023

As cameras have become primary sensors for mobile robots, vision based Simultaneous Localization and Mapping (SLAM) has achieved impressive results with the recent development of computer vision and deep learning. However, vision information has a disadvantage in that a lot of information disappears in a low-light environment. To overcome the problem, we propose an image enhancement method to perform visual SLAM in a low-light environment. Using the deep generative adversarial models and modified gamma correction, the quality of low-light images were improved. The proposed method is less sharp than the existing method, but it can be applied to ORB-SLAM in real time by dramatically reducing the amount of computation. The experimental results were able to prove the validity of the proposed method by applying to public Dataset TUM and VIVID++.

• Annual Conference of KIPS
• /
• 2023.11a
• /
• pp.563-565
• /
• 2023

Acupuncture and acupressure apply needles or pressure to anatomical points for therapeutic benefit. The over 350 mapped acupuncture points in the human body can each treat various conditions, but anatomical variations make precisely locating these acupoints difficult. We propose a computer vision technique using the real-time hand and face tracking capabilities of the MediaPipe framework to identify acupoint locations. Our model detects anatomical facial and hand landmarks, and then maps these to corresponding acupoint regions. In summary, our proposed model facilitates precise acupoint localization for self-treatment and enhances practitioners' abilities to deliver targeted acupuncture and acupressure therapies.

• Computers and Concrete
• /
• v.32 no.6
• /
• pp.615-623
• /
• 2023

Crack detection is an essential method to ensure the safety of dam concrete structures. Low-quality crack images of dam concrete structures limit the application of neural network methods in crack detection. This research proposes a modified attentional mechanism model to reduce the disturbance caused by uneven light, shadow, and water spots in crack images. Also, the focal loss function solves the small ratio of crack information. The dataset collects from the network, laboratory and actual inspection dataset of dam concrete structures. This research proposes a novel method for crack detection of dam concrete structures based on the U-Net neural network, namely AF-UNet. A mutual comparison of OTSU, Canny, region growing, DeepLab V3+, SegFormer, U-Net, and AF-UNet (proposed) verified the detection accuracy. A binocular camera detects cracks in the experimental scene. The smallest measurement width of the system is 0.27 mm. The potential goal is to achieve real-time detection and localization of cracks in dam concrete structures.

• International Journal of Control, Automation, and Systems
• /
• v.1 no.1
• /
• pp.119-126
• /
• 2003

The problem of tracking moving objects in a video stream is discussed in this pa-per. We discussed the popular technique of optical flow for moving object detection. Optical flow finds the velocity vectors at each pixel in the entire video scene. However, optical flow based methods require complex computations and are sensitive to noise. In this paper, we proposed a new method based on the Hough transform and on voting accumulation for improving the accuracy and reducing the computation time. Further, we applied the Boo-lean based edge detector for edge detection. Edge detection and segmentation are used to extract the moving objects in the image sequences and reduce the computation time of the CHT. The Boolean based edge detector provides accurate and very thin edges. The difference of the two edge maps with thin edges gives better localization of moving objects. The simulation results show that the proposed method improves the accuracy of finding the optical flow vectors and more accurately extracts moving objects' information. The process of edge detection and segmentation accurately find the location and areas of the real moving objects, and hence extracting moving information is very easy and accurate. The Combinatorial Hough Transform and voting accumulation based optical flow measures optical flow vectors accurately. The direction of moving objects is also accurately measured.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.10 no.2
• /
• pp.320-326
• /
• 2009

Providing visual field for a driver is one of the most important things for safe driving. Therefore, it will be a first step fur the safe driving that the driver recognizes front and back outside scenes within short time in the car. Specially, it is essential to take the visual field in frequently foggy area where the traffic accident can cause highest rank in the number of deaths. In this paper, our technique can provide the visual field by displaying the location of neighboring vehicles on the monitoring system, embedded board navigator in the car, using the location information of the vehicles from GPS(Global Positioning System) in real time. It is expected that this system can contribute to help safe driving and to lower collision accidents by guiding to cope with unexpected circumstances.

• Proceedings of the KIEE Conference
• /
• 2000.07d
• /
• pp.2784-2786
• /
• 2000

Mobile robots include control modules for autonomous obstacle avoidance and navigation. They are range modules to detect and avoid obstacles. motor control modules to operate two wheels. and encoder modules for localization. There is needed an appropriate controller for each modules. In this paper. a control system. including 18 channels for Sonar sensors. 4 channels for PWM modules. and 4 channels for encoder modules. is proposed using TMS320C32 DSP adopted with CAN. The board communicates with other modules by CAN. so that mobile robots can perform several tasks in real time. So we can realize on autonomous mobile robot with basic functions such as obstacle avoidance by using the developed controller. Especially. this controller has 100 msec scan time for 16 sonar sensors and can detect closer objects comparing with standard sonar sensors.

• Journal of Agricultural Extension & Community Development
• /
• v.7 no.2
• /
• pp.289-293
• /
• 2000

The way society works in the 21st century differs from that of 20th century, since the people are brought-up to speed regarding current technologies. The www.aflos.pe.kr site and direct e-mailing system were very useful in delivering floricultural information to extension educators, producers, and variety of individuals. The author’s one year experience indicated that extension educators and farmers are receptive to internet technologies, and extension educators have increased the knowledge base of their clientele by responding through direct e-mails. The internet and direct e-mailing systems were popular and powerful way of transferring floricultural information, especially agricultural extension manpower were limited because of localization of extension educators by changing national status to local governments and decreased number of extension educators through government restructuring. The direct e-mailing to approximately 503 individuals resulted about $1{\sim}3%$ responses and the number of phone calls, however virus protection software for e-mail, internet, file servers and desktops to provide the integrated real-time detection of viruses were needed. For more effective operation of direct e-mailing in the future, more specified target groups and specialized organization such as perennials, bulbs, flowering potted plants. and cut flowers. At the same time, things that have worked for last century should not be replaced with new technology, specifically, the value in one-on-one meetings should not be replaced, but rather serve as a supplement.

• Proceedings of the KIEE Conference
• /
• 2007.07a
• /
• pp.300-301
• /
• 2007

본 논문에서는 실시간 스펙트럼 추정기에 기반하여 시간-주파수 영역 반사파 계측 시스템에서의 동축케이블 결함을 검출하는 방법을 제안한다. 시간-주파수 영역 반사파 계측 시스템은 가우시안 포락선(Gaussian Envelop)모양의 첩 신호를 기준신호로 하여 도선에 반사파를 분석하는 기법으로써 타 방법에 비하여 높은 정확도를 자랑하는 것으로 알려져 있다. 하지만 결함 위치를 추정하기 위해 Wigner 시간 주파수 분포 함수를 이용하므로 계산량 증가에 따른 실시간 구현이 어렵다는 단점이 있었다. 이러한 단점을 극복하기 위하여 본 논문에서는 LMS 스펙트럼 추정기를 이용한 시간-주파수 영역 반사파 계측 시스템의 구현방법을 새롭게 제안한다. 제안된 기법은 실제 동축케이블에 대한 실험결과를 통하여 그 성능을 입증하도록 한다.

• The Journal of the Korea institute of electronic communication sciences
• /
• v.14 no.4
• /
• pp.637-644
• /
• 2019

This paper describes an implementation of a graph-based simultaneous localization and mapping(SLAM) method called the General Graph Optimization. The General Graph Optimization formulates the SLAM problem using nodes and edges. The nodes represent the location and attitude of a robot in time sequence, and the edge between the nodes depict the constraint between the nodes. The constraints are imposed by sensor measurements. The General Graph Optimization solves the problem by optimizing the performance index determined by the constraints. The implementation is verified using the measurement data sets which are open for test of various SLAM methods.

• IEMEK Journal of Embedded Systems and Applications
• /
• v.19 no.5
• /
• pp.235-242
• /
• 2024

In the context of urban autonomous driving, where various types of traffic lights are encountered, traffic light recognition technology is of paramount importance. We have designed a high-performance traffic light recognition module tailored to scenarios encountered in domestic urban driving and devised a dataset construction process. In this paper, we focus on minimizing the camera's dependency to enhance traffic light recognition performance. The camera is used solely to distinguish the color information of traffic lights, while accurate location information of the traffic lights is obtained through localization and a map. Based on the information from these components, camera RoIs (Region of Interest) are extracted and transmitted to the embedded board. The transmitted images are then sent back to the main system for autonomous driving control. The processing time for one traffic light RoI averages 43.2 ms. We achieve processing times of average 93.4 ms through batch inference to meet real-time requirements. Additionally, we design a data construction process for collecting, refining, and storing traffic light datasets, including semi-annotation-based corrections.