Omni-Vision System of Intelligent Car Based on DSP & FPGA

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In order to realize omni-vision system of intelligent car for auto wandering in real-time processing, an image processing system with 6 vision channels based on FPGA&DSP is designed. In the system, two ZBT SRAM chips are used as the input and output cache for high data transferring. A FPGA chip is responsible for the core logic controlling and video synchronous. Digital videos are sent so processing module by camlink bus. Data are exchanged by EMIF and McBSP between FPGA and DSPs. EDMA is used for data transferring between SRAM in FPGA and ZBT SRAM. The QDMA is used for 2D data transferring to 1D into DSP cache. Tasks are assigned to chips by μC/OS on master DSP. All this together, real-time data sampling and processing for multi-channel vision was realized.

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109-114

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June 2012

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© 2012 Trans Tech Publications Ltd. All Rights Reserved

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[1] R. C. Chaubey. Computerized Image Analysis Software for the Comet Assay, Molecular Toxicology Protocols, ISSN 1064-3745, (2008).

DOI: 10.1385/1-59259-840-4:097

Google Scholar

[2] JinSeon Youn, JunRim Choi, Seung-Soo Han, Parallel Integer Motion Estimation Method by Using Reference Blocks Shared for HD Video Encoding, International Conference on Electronic Computer Technology, ISBN: 978-0-7695-3559-3, IEEE Computer Soc, CA, USA, Feb. 2009: pp.577-581.

DOI: 10.1109/icect.2009.9

Google Scholar

[3] M. Fikret Ercan. Parallel Image Understanding on a Multi-DSP System. O. Gervasi and M. Gavrilova (Eds. ): ICCSA 2007, LNCS 4706, Part II, p.1¨C12, 2007. Springer-Verlag Berlin Heidelberg (2007).

Google Scholar

[4] Shirvaikar Mukul1 ; Bushnaq, Tariq1 , A comparison between DSP and FPGA platforms for real-time imaging applications, Proceedings of SPIE-IS and T Electronic Imaging - Real-Time Image and Video Processing, (2009).

DOI: 10.1117/12.806099

Google Scholar

[5] Davis, L.S.: Foundations of Image Understanding. Springer, Heidelberg (2001).

Google Scholar

[6] Kumar, V.P., Wang, C.L.: Parallelism for Image Understanding. In: Zomaya, A.D. (ed. ) Parallel and Distributed Computing Handbook, p.1042¨C1070. Mcgraw-Hill, New York (1996).

Google Scholar

[7] HLI Ji-kuiH, HXIANG Huai-kunH, HHU HongH. Research on video image processing system based on uCOS -Ⅱ. Journal of Harbin Institut of Technology. H Vol. 39, No. 2, H2007.

Google Scholar