Image Link Through Adaptive Encoding Data Base and Optimized GPU Algorithm for Real-time Image Processing of Artificial Intelligence


  • Byoungman An Electronic and Electrical Engineering, Dankook University, 152, Jukjeon-ro, Suji-gu, Yongin-si, Gyeonggi-do, 16890, Korea
  • Youngseop Kim Electronic and Electrical Engineering, Dankook University, 152, Jukjeon-ro, Suji-gu, Yongin-si, Gyeonggi-do, 16890, Korea



Image Link, In-vehicle, GPU Algorithm Optimization, Audio Video Bridge, AVB, Low Latency, Automotive, Multimedia, Artificial Intelligence, Data Base


This paper presents the latest Ethernet standardization of in-vehicle network and the future trends of automotive ethernet technology. The proposed system provides a design and optimization algorithm of in-vehicle networking technologies related Ethernet Audio Video Bridge (AVB) 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 Machin to Machine (RLMM) plays a significant role in reducing the latency between devices. The approach of RLMM on realistic test cases indicated that there was a latency reduction about 30.41% It is expected that the optimized settings for the actual automotive network environment can greatly shorten the time period in the development and design process. The results achieved from the experiments on the latency present in each function are trustworthy since average values are obtained via repeated tests for several months. It would considerably benefit the industry because analyzing the delay between each function in a short period of time is tremendously significant. In addition, through the proposed real-time camera and video streaming via optimized settings of AVB system, it is expected that AI (Artificial Intelligence) algorithms in autonomous driving will be of great help in understanding and analyzing images in real time.


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Author Biographies

Byoungman An , Electronic and Electrical Engineering, Dankook University, 152, Jukjeon-ro, Suji-gu, Yongin-si, Gyeonggi-do, 16890, Korea

Byoungman An received the B.S. and M.S. in Electronics & Electrical Engineering from Dankook University, Korea in 2010 and 2012, respectively. He is also currently pursuing an Ph.D. degree in the school of Electrical & Electronics Engineering. His research interests include image/video compression, automotive network, in-vehicle network and image processing.

Youngseop Kim, Electronic and Electrical Engineering, Dankook University, 152, Jukjeon-ro, Suji-gu, Yongin-si, Gyeonggi-do, 16890, Korea

Youngseop Kim received the M.S in Computer Engineering from the University of Southern California in 1991, and the Ph.D. in Electronic Systems from Rensselaer Polytechnic Institute in 2001. He was a manager at Samsung SDI until 2003. He developed the image-processing algorithm for PDP TV while at Samsung. Currently he is a Professor at Dankook University in Korea. He is the resolution member and the Editor of JPsearch part 2 in JPEG, the co-Chair of JPXML in JPEG, and Head of Director (HOD) of Korea. He is also Editor-in-chief of the Korea Semiconductor and Technology Society. His research interests are in the areas of image/video compression, pattern recognition, communications, stereoscopic codecs, and augment reality. They include topics such as object-oriented methods for image/video coding, joint source-channel coding for robust video transmission, rate control, video transmission over packet wired or wireless networks, pattern recognition, and image processing.


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