Abstract
Traffic sign recognition (TSR), taken as an important component of an intelligent vehicle system, has been an emerging research topic in recent years. In this paper, a traffic sign detection system based on color segmentation, speeded-up robust features (SURF) detection and the k-nearest neighbor classifier is introduced. The proposed system benefits from the SURF detection algorithm, which achieves invariance to rotated, skewed and occluded signs. In addition to the accuracy and robustness issues, a TSR system should target a real-time implementation on an embedded system. Therefore, a hardware/software co-design architecture for a Zynq-7000 FPGA is presented as a major objective of this work. The sign detection operations are accelerated by programmable hardware logic that searches the potential candidates for sign classification. Sign recognition and classification uses a feature extraction and matching algorithm, which is implemented as a software component that runs on the embedded ARM CPU.
Highlights
IntroductionElectronics 2015, 4 change in car design and driver assistance systems
Emerging technologies, such as vehicle-to-vehicle communications (V2V) [1], in-car cellular connectivity [2] and increased computational prowess of embedded processors, are heralding a revolutionaryElectronics 2015, 4 change in car design and driver assistance systems
One of the key goals of this work is to develop an efficient combination of a software processing system (C code running on CPU cores) and an field programmable gate arrays (FPGAs) logic for hardware acceleration and control
Summary
Electronics 2015, 4 change in car design and driver assistance systems. These technologies will play a key role in the development of self-driving cars in the near future [3,4]. A key component of advanced driver assistance systems is traffic sign recognition (TSR) that enables the car to recognize the road signs in real-world environments. Successful detection and recognition of traffic signs can be used to alert the driver and/or to facilitate autonomous driving operations. The main challenge for robust detection performance comes from the complexity of the environment, such as lighting conditions, weather conditions, similar color background and occlusions. Real-time operation is another challenge for the TSR system. A system that can provide sign information even at high traveling speeds is necessary for driver assistance systems
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