• Journal of the Institute of Convergence Signal Processing
• /
• v.22 no.2
• /
• pp.85-90
• /
• 2021

A ADAS(Advanced Driver Assistance System) for the safe driving is an important area in autonumous car. Specially, a ADAS software using an image sensors attached in previous car is low in building cost, and utilizes for various purpose. A algorithm for detecting the break-lamp from the tail-lamp of preceding vehicle is proposed in this paper. This method can perceive the driving condition of preceding vehicle. Proposed method uses the YOLO techinicque that has a excellent performance in object tracing from real scene, and extracts the intensity variable region of break-lamp from HSV image of detected vehicle ROI(Region Of Interest). After detecting the candidate region of break-lamp, each isolated region is labeled. The break-lamp region is detected finally by using the proposed selective-attention model that percieves the shape-similarity of labeled candidate region. In order to evaluate the performance of the preceding vehicle break-lamp detection system implemented in this paper, we applied our system to the various driving images. As a results, implemented system showed successful results.

• Journal of the Institute of Convergence Signal Processing
• /
• v.21 no.3
• /
• pp.127-132
• /
• 2020

In this study, the process of providing information necessary to remove physical barriers such as road slopes that obstruct the activities of the disabled is in progress. Through experiments, we implement a quantified road surface roughness index that enables the implementation of IoT-based systems necessary for the elderly and the disabled to safely move to their destination. As a preliminary study, a road surface measurement device using a gyroscope was devised. To check the roughness and flatness of the road surface, X, Y displacement, and acceleration displacement were measured using a gyroscope. By calculating the measured data, the roughness and flatness of the road surface were quantified from 0 to 100. We implemented an algorithm that divides this index into 4 stages, displays it on a map, and provides it to users. Finally, a system for the disabled and elderly electric wheelchair users to secure basic mobility was established.

• Journal of Practical Engineering Education
• /
• v.12 no.2
• /
• pp.309-319
• /
• 2020

Billiards is a fun and popular sport, but both route planning and cueing prevent beginners from becoming skillful. A beginner in billiards requires constant concentration and training to reach the right level, but without the right motivating factor, it is easy to lose interests. This study aims to induce interest in billiards and accelerate learning by utilizing billiard path prediction and visualization on a highly immersive augmented reality platform that combines a stereo camera and a VR headset. For implementation, the placement of billiard balls is recognized through the OpenCV image processing program, and physics simulation, path search, and visualization are performed in Unity Engine. As a result, accurate path prediction can be achieved. This made it possible for beginners to reduce the psychological burden of planning the path, focus only on accurate cueing, and gradually increase their billiard proficiency by getting used to the path suggested by the algorithm for a long time. We confirm that the proposed AR billiards is remarkably effective as a learning assistant tool.

• Journal of Convergence for Information Technology
• /
• v.11 no.3
• /
• pp.1-6
• /
• 2021

Most of the match-3 puzzle games supports automatic play using the MCTS algorithm. However, implementing reinforcement learning agents is not an easy job because it requires both the knowledge of machine learning and the way of complex interactions within the development environment. This study proposes a method in which we can easily design reinforcement learning agents and implement game play agents by applying PPO(Proximal Policy Optimization) algorithms. And we could identify the performance was increased about 44% than the conventional method. The tools we used are the Unity 3D game engine and Unity ML SDK. The experimental result shows that agents became to learn game rules and make better strategic decisions as experiments go on. On average, the puzzle gameplay agents implemented in this study played puzzle games better than normal people. It is expected that the designed agent could be used to speed up the game level design process.

• Smart Media Journal
• /
• v.10 no.1
• /
• pp.32-38
• /
• 2021

Image classification through deep learning on the image from photographs has been a very active research field for the past several years. In this paper, we propose a method of automatically discriminating stone images from domestic source through deep learning, which is to use Python's hash library to scan 300×300 pixel photo images of granites such as Hwangdeungseok, Goheungseok, and Pocheonseok, performing data preprocessing to create learning images by examining duplicate images for each stone, removing duplicate images with the same hash value as a result of the inspection, and deep learning by stone. In addition, to utilize VGGNet, the size of the images for each stone is resized to 224×224 pixels, learned in VGG16 where the ratio of training and verification data for learning is 80% versus 20%. After training of deep learning, the loss function graph and the accuracy graph were generated, and the prediction results of the deep learning model were output for the three kinds of stone images.

• Journal of Cadastre & Land InformatiX
• /
• v.51 no.1
• /
• pp.67-77
• /
• 2021

Spatial data is becoming very important as a medium that connects various data produced in smart cities, digital twins, autonomous driving, smart construction, and other applications. In addition, the rapid construction and update of spatial information is becoming a hot topic to satisfy the diverse needs of consumers in this field. This study developed a software prototype that can match the position of an image-based 3D building model produced without Ground Control Points using existing spatial data. As a result of applying this software to the test area, the 3D building model produced based on the image and the existing spatial data show a high positional matching rate, so that it can be widely used in applications requiring the latest 3D spatial data.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.20 no.4
• /
• pp.95-105
• /
• 2021

Road surface damage detection is essential for a comfortable driving environment and the prevention of safety accidents. Road management institutes are using automated technology-based inspection equipment and systems. As one of these automation technologies, a sensor to detect road surface damage plays an important role. For this purpose, several studies on sensors using deep learning have been conducted in recent years. Road images and label images are needed to develop such deep learning algorithms. On the other hand, considerable time and labor will be needed to secure label images. In this paper, the adversarial learning method, one of the semi-supervised learning techniques, was proposed to solve this problem. For its implementation, a lightweight deep neural network model was trained using 5,327 road images and 1,327 label images. After experimenting with 400 road images, a model with a mean intersection over a union of 80.54% and an F1 score of 77.85% was developed. Through this, a technology that can improve recognition performance by adding only road images was developed to learning without label images and is expected to be used as a technology for road surface management in the future.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.26 no.3
• /
• pp.396-402
• /
• 2022

User interactions are being developed in various forms, and in particular, interactions using human gestures are being actively studied. Among them, hand gesture recognition is used as a human interface in the field of realistic media based on the 3D Hand Model. The use of interfaces based on hand gesture recognition helps users access media media more easily and conveniently. User interaction using hand gesture recognition should be able to view images by applying fast and accurate hand gesture recognition technology without restrictions on the computer environment. This paper developed a fast and accurate user hand gesture recognition algorithm using the open source media pipe framework and machine learning's k-NN (K-Nearest Neighbor). In addition, in order to minimize the restriction of the computer environment, a stereoscopic image control system based on user hand gesture recognition was designed and implemented using a web service environment capable of Internet service and a docker container, a virtual environment.

• Journal of Convergence for Information Technology
• /
• v.12 no.4
• /
• pp.1-8
• /
• 2022

With the development of communication infrastructure, the number of network equipment owned by one person is gradually increasing. General-purpose devices such as smartphones can implement theft/loss prevention function by implementing S/W. However, other small devices lack practicality such as long-distance communication problems due to standard communication technology specifications or H/W limitations, and lack of functions(authentication and security). This study combines the Lora communication protocol in the LPWA standard environment and the blockchain technology. Anti-theft and security functions were added to the protocol, and the PBFT consensus algorithm was applied to build a blockchain network. As a result of the test, the effectiveness of safety(authentication and trust network) and performance(blockchain processing performance) were confirmed. This study aims to contribute to the future development of portable or small device anti-theft products as a 4th industrial convergence research.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.26 no.3
• /
• pp.422-429
• /
• 2022

In this paper, the intermediate frequency transmission signal level between the network system-based baseband and RF unit consisting of multi-channel airborne relay devices and a lot of mission devices, which are currently undergoing technology development tasks, is kept constant at the reference signal level. Considering the other party's receiving input range, despite changes in the short-range long-range wireless communication environment, it presents a multi-link protection and MLP-A algorithm that allows signals to be transmitted stably and reliably through signal detection automatic gain control, and experiments and analysis considering short-distance and long-distance wireless environments were performed by designing, manufacturing, and implementing RF units to which MLP-A algorithms were applied, and applying distance calculation equations to the configuration of multiple air movements and verification networks. Through this, it was confirmed that a stable and reliable RF communication system can be operated.