• Journal of the Korea Institute of Military Science and Technology
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• v.24 no.1
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• pp.31-40
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• 2021

The multi-channel video streaming system is an essential device for future ground combat vehicles. For the system, the application of digital interfaces is required instead of the direct analog method to support selectable multiple channels. However, due to the characteristics of the digital interfaces that require en/decoding and signal conversion, the system should support the ability to adapt to quality and delay requirements depending on how video data is utilized. To support addressed issue, this study designs and emulates the multi-channel compressed-video streaming system of ground combat vehicle's fire control system based on commercial standards. Using the system, this study analyzes the quality of video according to the rotational speed of the acquisition device and Glass-to-Glass (G2G) delay between video acquisition and display devices according to video compression rates. Through these experiments and analysis, this paper presents the design direction of the system having scalability on the latest technology while providing high-quality video data streaming flexibly.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.8
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• pp.3025-3047
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• 2021

This paper presents the latest Ethernet standardization of in-vehicle network and the future trends of automotive Ethernet technology. The proposed system provides design and optimization algorithms for automotive networking technology related to AVB (Audio Video Bridge) technology. We present a design of in-vehicle network system as well as the optimization of AVB for automotive. A proposal of Reduced Latency of Machine to Machine (RLMM) plays an outstanding role in reducing the latency among devices. RLMM's approach to real-world experimental cases indicates a reduction in latency of around 41.2%. The setup optimized for the automotive network environment is expected to significantly reduce the time in the development and design process. The results obtained in the study of image transmission latency are trustworthy because average values were collected over a long period of time. It is necessary to analyze a latency between multimedia devices within limited time which will be of considerable benefit to the industry. Furthermore, the proposed reliable camera and video streaming through optimized AVB device settings would provide a high level of support in the real-time comprehension and analysis of images with AI (Artificial Intelligence) algorithms in autonomous driving.

• Journal of information and communication convergence engineering
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• v.20 no.3
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• pp.226-233
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• 2022

Video surveillance is widely used in security surveillance, military navigation, intelligent transportation, etc. Its main research fields are pattern recognition, computer vision and artificial intelligence. This article uses OpenCV to detect and track vehicles, and monitors by establishing an adaptive model on a stationary background. Compared with traditional vehicle detection, it not only has the advantages of low price, convenient installation and maintenance, and wide monitoring range, but also can be used on the road. The intelligent analysis and processing of the scene image using CAMSHIFT tracking algorithm can collect all kinds of traffic flow parameters (including the number of vehicles in a period of time) and the specific position of vehicles at the same time, so as to solve the vehicle offset. It is reliable in operation and has high practical value.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.42 no.4
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• pp.892-898
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• 2017

This paper describes the development of AVN(Audio Video Navigation) software for vehicle information analysis and gesture recognition. The module that examine the CAN(Controller Area Network) data of vehicle in the designed software analyzes the driving state. Using classified information, the AVN software converge vehicle information and hand gesture information. As the result, the derived data is used to match the service step and to perform the service. The designed AVN software was implemented in HW platform that common used in vehicles. And we confirmed the operation of vehicle analysing module and gesture recognition in a simulated environment that is similar with real world.

• Journal of Broadcast Engineering
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• v.19 no.6
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• pp.798-809
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• 2014

Video stabilization is performed to remove unexpected shaky and irregular motion from a video. It is often used as preprocessing for robust feature tracking and matching in video. Typical video stabilization algorithms are developed to compensate motion from surveillance video or outdoor recordings that are captured by a hand-help camera. However, since the vehicle video contains rapid change of motion and local features, typical video stabilization algorithms are hard to be applied as it is. In this paper, we propose a novel approach to compensate shaky and irregular motion in vehicle video using linear regression model and vertical projection histogram matching. Towards this goal, we perform vertical projection histogram matching at each sub region of an input frame, and then we generate linear regression model to extract vertical translation and rotation parameters with estimated regional vertical movement vector. Multiple binarization with sub-region analysis for generating the linear regression model is effective to typical recording environments where occur rapid change of motion and local features. We demonstrated the effectiveness of our approach on blackbox videos and showed that employing the linear regression model achieved robust estimation of motion parameters and generated stabilized video in full automatic manner.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.7A
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• pp.807-813
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• 2004

This paper corresponded to Smart-UAV(Smart Unmanned Aerial Vehicle) technology development, a part of “The 21th Century New-Frontier Development Project” being propelled in accordance with enlarging the necessity of concentration development by selecting our strong technique being able to compete in the international society of knowledge based economy in the 21th century. Also, we designed Ku-band airborne video transceiver system performing to receive the TC(Tele-Command) signal needed to be applicable of Smart-UAV, and send the video and TM(Tele-Metry) signal at the same time. Moreover, we analyzed it in order to satisfy the system request of designed whole communication system, and established the validity on this paper going through by module simulation and manufacture of the whole system.

• Journal of the Semiconductor & Display Technology
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• v.13 no.1
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• pp.27-33
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• 2014

Video from unmanned aerial vehicle (UAV) is influenced by natural environments due to the light-weight UAV, specifically by winds. Thus UAV's shaking movements make the video shaking. Objective of this paper is making a stabilized video by removing shakiness of video acquired by UAV. Stabilizer estimates camera's motion from calculation of optical flow between two successive frames. Estimated camera's movements have intended movements as well as unintended movements of shaking. Unintended movements are eliminated by smoothing process. Experimental results showed that our proposed method performs almost as good as the other off-line based stabilizer. However estimation of camera's movements, i.e., calculation of optical flow, becomes a bottleneck to the real-time stabilization. To solve this problem, we make parallel stabilizer making average 30 frames per second of stabilized video. Our proposed method can be used for the video acquired by UAV and also for the shaking video from non-professional users. The proposed method can also be used in any other fields which require object tracking, or accurate image analysis/representation.

• Journal of the Korea Society of Computer and Information
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• v.20 no.6
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• pp.87-97
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• 2015

An Aerial video summarization is not only the key to effective browsing video within a limited time, but also an embedded cue to efficiently congregative situation awareness acquired by unmanned aerial vehicle. Different with previous works, we utilize sensor operation mode of unmanned aerial vehicle, which is global, local, and focused surveillance mode in order for accurately summarizing the aerial video considering flight and surveillance/reconnaissance environments. In focused mode, we propose the moving-react tracking method which utilizes the partitioning motion vector and spatiotemporal saliency map to detect and track the interest moving object continuously. In our simulation result, the key frames are correctly detected for aerial video summarization according to the sensor operation mode of aerial vehicle and finally, we verify the efficiency of video summarization using the proposed mothed.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.1
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• pp.475-481
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• 2014

Recently, it is used to apply various improved methods to determine the cause of traffic accidents. However, most of vehicle black box usually start to store the video information by an event trigger in case that the impact value at that time exceeds the threshold impact value as compared the threshold impact value saved in advance with the current impact value. there are problems with above method that a lot video information should be saved in the memory card of the vehicle black box, and the user should delete the unwanted video information every time because of unclassified video store. In this paper, we propose the ontology-based context aware algorithm that the vehicle black box recognize the situation, and then remove the video data with a low weighting factor by itself for efficient memory management.

• Journal of the Semiconductor & Display Technology
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• v.21 no.1
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• pp.22-26
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• 2022

This paper proposes a new method for the recognition of road surface marks and numbers. The proposed method designates a region of interest on the road surface without first detecting a lane. The road surface markings are extracted by location and size using a connection component analysis. Distortion due to the perspective effect is minimized by normalizing the size of the road markings. The road surface marking of the connected component is recognized by matching it with the stored road marking templates. The proposed method is implemented using C language in Raspberry Pi 4 system with a camera module for a real-time image processing. The system was fixedly installed in a moving vehicle, and it recorded a video like a vehicle black box. Each frame of the recorded video was extracted, and then the proposed method was tested. The results show that the proposed method is successful for the recognition of road surface marks and numbers.