Front vehicle detection based on parallel Blob detection using quad-pipeline on FPGA. (28th November 2019)

• Record Type: Journal Article
• Authors: Nojiri, Naoto; Masaki, Seben; Meng, Lin; Shimakawa, Hiromitsu; Yamazaki, Katsuhiro
• Is Part Of: International journal of modelling, identification and control. Volume 33:Number 1(2020)
• Page Start: 20
• Page End: 27
• Publication Date: 2019-11-28
• Subjects: FPGA -- front vehicle detection -- quad-pipeline -- scalability; Engineering -- Methodology -- Periodicals; Science -- Methodology -- Periodicals; 001.42
• Languages: English
• ISSNs: 1746-6172

Abstract

Real-time front vehicle detection is one of the important topics in intelligent transport systems. FPGA is an effective hardware device for high performance computing. This paper describes real-time front vehicle detection using quad-pipeline image processing on FPGA for intelligent transport systems. Front vehicle detection is implemented based on tail lights detection and white lines detection. When the two red Blobs of tail lights are detected between the two white line Blobs, the front vehicle is determined. For achieving real-time image processing on FPGA, the image is divided into four parts and the four image processing are realized by four-stage-pipeline. In detail, tail lights are detected using two pipelines, and white lines are detected using the other two pipelines. The experimental results show that the quad-pipeline system can detect a vehicle up ahead in 124.8 μ s on Artix7, which is 1.91 times faster than the dual-pipeline one.