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

Authors

  • Byoungman An Electronic and Electrical Engineering, Dankook University, 152, Jukjeon-ro, Suji-gu, Yongin-si, Gyeonggi-do, 16890, Korea https://orcid.org/0000-0002-4127-0651
  • Youngseop Kim Electronic and Electrical Engineering, Dankook University, 152, Jukjeon-ro, Suji-gu, Yongin-si, Gyeonggi-do, 16890, Korea

DOI:

https://doi.org/10.13052/jwe1540-9589.21215

Keywords:

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

Abstract

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.

References

IEEE Standard for Local and metropolitan area networks, “Audio Video Bridging (AVB) Systems,” in IEEE Std 802.1BA-2011, vol., no., pp. 1–45, 30 Sept. 2011.

IEEE Standard for Local and Metropolitan Area Networks, “Timing and Synchronization for Time-Sensitive Applications in Bridged Local Area Networks,” in IEEE Std 802.1AS-2011, vol., no., pp. 1–292, 30 March 2011.

J. Eveleens, “Ethernet AVB Overview and Status,” SMPTE 2014 Annual Technical Conference & Exhibition, Hollywood, CA, USA, 2014, pp. 1–11.

C. Herber, A. Saeed and A. Herkersdorf, “Design and Evaluation of a Low-Latency AVB Ethernet Endpoint Based on ARM SoC,” 2015 IEEE 17th International Conference on High Performance Computing and Communications, 2015 IEEE 7th International Symposium on Cyberspace Safety and Security, and 2015 IEEE 12th International Conference on Embedded Software and Systems, New York, NY, 2015, pp. 1128–1134.

T. Nolte, H. Hansson and L. L. Bello, “Automotive communications-past, current and future,” 2005 IEEE Conference on Emerging Technologies and Factory Automation, Catania, 2005, pp. 8–992.

R. Queck, “Analysis of Ethernet AVB for automotive networks using Network Calculus,” 2012 IEEE International Conference on Vehicular Electronics and Safety (ICVES 2012), Istanbul, 2012, pp. 61–67.

J. Park, B. Cheoun and J. Jeon, “Worst-case analysis of ethernet AVB in automotive system,” 2015 IEEE International Conference on Information and Automation, Lijiang, 2015, pp. 1696–1699.

X. Liu, Z. Nie, D. Li and H. Yu, “Design of An Improved Ethernet AVB Model for Real-time Communication in In-Vehicle Network,” 2019 IEEE 3rd Information Technology, Networking, Electronic and Automation Control Conference (ITNEC), Chengdu, China, 2019, pp. 6–10.

D. An, “Design and implementation of the car multimedia data transmission system using Ethernet AVB,” 2016 Eighth International Conference on Ubiquitous and Future Networks (ICUFN), Vienna, 2016, pp. 481–483.

O. Kleineberg, P. Fröhlich and D. Heffernan, “Fault-tolerant Audio and Video Bridging (AVB) Ethernet: A novel method for redundant stream registration configuration,” Proceedings of 2012 IEEE 17th International Conference on Emerging Technologies & Factory Automation (ETFA 2012), Krakow, 2012, pp. 1–8.

L. Zhao, P. Pop, Z. Zheng and Q. Li, “Timing Analysis of AVB Traffic in TSN Networks Using Network Calculus,” 2018 IEEE Real-Time and Embedded Technology and Applications Symposium (RTAS), Porto, 2018, pp. 25–36.

J. Imtiaz, J. Jasperneite and L. Han, “A performance study of Ethernet Audio Video Bridging (AVB) for Industrial real-time communication,” 2009 IEEE Conference on Emerging Technologies & Factory Automation, Mallorca, 2009, pp. 1–8.

F. Reimann, S. Graf, F. Streit, M. Glaß and J. Teich, “Timing analysis of Ethernet AVB-based automotive E/E architectures,” 2013 IEEE 18th Conference on Emerging Technologies & Factory Automation (ETFA), Cagliari, 2013, pp. 1–8.

S. Jeon, J. Lee and S. Park, “Dual-path method for enhancing the performance of IEEE 802.1 avb with time-triggered scheme,” 2015 21st Asia-Pacific Conference on Communications (APCC), Kyoto, 2015, pp. 519–523.

Virtual Bridged Local Area Networks – Amendment 9: Stream Reservation Protocol (SRP), IEEE P802.1Qat/D6.1 edition, June 2010.

Virtual Bridged Local Area Networks – Amendment 12: Forwarding and Queuing Enhancements for Time-Sensitive Streams, IEEE P802.1Qav/D7.0 edition, October 2009.

A. Kern, H. Zinner, T. Streichert, J. Nöbauer and J. Teich, “Accuracy of Ethernet AVB time synchronization under varying temperature conditions for automotive networks,” 2011 48th ACM/EDAC/IEEE Design Automation Conference (DAC), New York, NY, 2011, pp. 597–602.

J. M. Ready and C. N. Taylor, “GPU Acceleration of Real-time Feature Based Algorithms,” 2007 IEEE Workshop on Motion and Video Computing (WMVC’07), Austin, TX, USA, 2007, pp. 8–8.

B. An, Y. Kim and O. Kwon, “Low-Complexity Motion Estimation for H.264/AVC Through Perceptual Video Coding,” KSII Transactions on Internet and Information Systems, vol. 5, no. 8, pp. 1444–1456, 2011.

D. Chai and K. N. Ngan, “Foreground/background video coding scheme,” ISCAS’97., Proceedings of 1997 IEEE International Symposium on, vol. 2, pp. 1448–1451, 1997.

R. R. Knipling et al., “Assessment of IVHS countermeasures for collision avoidance systems,” National Highway Traffic Safety Administration, Washington, DC, USA, Tech. Rep. DOT HS 807 995, May 1993.

T. Kim and H. Jeong, “A Novel Algorithm for Crash Detection Under General Road Scenes Using Crash Probabilities and an Interactive Multiple Model Particle Filter,” in IEEE Transactions on Intelligent Transportation Systems, vol. 15, no. 6, Dec. 2014.

B. An, Y. Kim, “Improved Crash Detection Algorithm for Vehicle Crash Detection,” KSDT vol. 19, no. 3. pp. 93–99, 2020.

T. Cohrs and L. Treybig, “Array microphones and signal processing within an ethernet-based AVB network,” 2016 IEEE 6th International Conference on Consumer Electronics - Berlin (ICCE-Berlin), 2016.

M. Kim, Y. Jang, M. Jung and S. Kim, “Frame Forwarding Rules for Link Utilization in IEEE 802.1 AVB Networks,” 2008 International Conference on Advanced Language Processing and Web Information Technology, 2008.

H. Lee, J. Lee, C. Park and S. Park, “Time-aware preemption to enhance the performance of Audio/Video Bridging (AVB) in IEEE 802.1 TSN,” 2016 First IEEE International Conference on Computer Communication and the Internet (ICCCI), 2016.

H. J. Rivera Verduzco, P. J. L. Cuijpers and J. Cao, “Work-in-Progress: Best-Case Response Time Analysis for Ethernet AVB,” 2017 IEEE Real-Time Systems Symposium (RTSS), 2017.

Y. S. Lee, J. H. Kim and J. W. Jeon, “FlexRay and Ethernet AVB Synchronization for High QoS Automotive Gateway,” in IEEE Transactions on Vehicular Technology, vol. 66, no. 7, pp. 5737–5751, July 2017.

Ms. M. Manju, P. Abarna, U. Akila, S. Yamini, “Peak Signal to Noise Ratio & Mean Square Error calculation for various Images using the lossless Image,” International Journal of Pure and Applied Mathematics, Volume 119, No. 12, 2018, 14471–14477, 2018.

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Published

2022-01-22

How to Cite

An , B. ., & Kim, Y. . (2022). Image Link Through Adaptive Encoding Data Base and Optimized GPU Algorithm for Real-time Image Processing of Artificial Intelligence. Journal of Web Engineering, 21(02), 459–496. https://doi.org/10.13052/jwe1540-9589.21215

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Section

SPECIAL ISSUE ON Future Multimedia Contents and Technology on Web in the 5G Era