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Smart Sensors and Systems pp 175–206Cite as

Intelligent Vision Processing Technology for Advanced Driver Assistance Systems

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Abstract

Intelligent vision processing technology has a wide range of applications on vehicles. Many of these applications are related to a so-called Advanced Driver Assistance System (ADAS). Collaborated with cameras, Pedestrian and Motorcyclist Detection System (PMD), Lane Departure Warning System (LDWS), Forward Collision Warning System (FCWS), Speed Limit Detection System (SLDS), and Dynamic Local Contrast Enhancement (DLCE) techniques can help drivers notice important events or objects around. This chapter gives an in-depth exploration for these intelligent vision processing technologies from the viewpoints of methodology development, algorithm optimization, and system implementation on embedded platforms. More precisely, this chapter tends to first give a survey and overview for newly appeared state-of-the-art intelligent vision processing technologies for ADAS, and then highlights some significant technologies including PMD, LDWS, FCWS, SLDS, and DLCE developed in System on Chip (SoC) Laboratory, Fong-Chia University, Taiwan, and intelligent Vision System (iVS) Laboratory, National Chiao Tung University, Taiwan. Besides, implementation and verification of the above ADAS technologies will also be presented. In summary, the proposed PMD design achieves 32.5 frame per second (fps) for 720 × 480 (D1) resolution on an AMD A10-7850K processor by using heterogeneous computing. On an automotive-grade Freescale i.MX6 (including 4-core ARM Cortex A9, 1 GB DDR3 RAM, and Linux environment) platform, the proposed LDWS, FCWS, and SLDS designs, respectively, achieve 33 fps, 32 fps, and 30 fps for D1 resolution. Finally, the proposed DLCE system is realized on a TREK-668 platform with an Intel Atom 1.6 GHz processor for real-time requirement of 50 fps at D1 resolution.

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Authors and Affiliations

  1. Department of Electronics Engineering, National Chiao Tung University, Hsinchu City, Taiwan

    Po-Chun Shen, Jui-Sheng Lee, Guan-Yu Chen, Yi-Ting Lin, Bing-Yang Cheng, Guo-An Jian, Hsiu-Cheng Chang & Jiun-In Guo

  2. Department of Electronics Engineering, Feng Chia University, Taichung City, Taiwan

    Kuan-Hung Chen & Wei-Ming Lu

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  1. Po-Chun Shen
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  2. Kuan-Hung Chen
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  3. Jui-Sheng Lee
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Correspondence to Kuan-Hung Chen .

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Editors and Affiliations

  1. Center for Integrated Smart Sensors, Yuseong-gu, Daejeon, Korea (Republic of)

    Chong-Min Kyung

  2. System LSI Research Center, Kyushu University, Fukuoka, Japan

    Hiroto Yasuura

  3. Circuits and Systems Division, Tsinghua University, Beijing, China

    Yongpan Liu

  4. National Tsing Hua University , Hsichu, Taiwan

    Youn-Long Lin

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Shen, PC. et al. (2017). Intelligent Vision Processing Technology for Advanced Driver Assistance Systems. In: Kyung, CM., Yasuura, H., Liu, Y., Lin, YL. (eds) Smart Sensors and Systems. Springer, Cham. https://doi.org/10.1007/978-3-319-33201-7_8

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  • DOI: https://doi.org/10.1007/978-3-319-33201-7_8

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