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Implementation of lane detection system using optimized hough transform circuit

机译:使用优化Hough变换电路的车道检测系统的实现

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This paper describes a vision-based lane detection system with the optimized Hough Transform circuit. The Hough Transform is a popular method to find the line features in an image. This is very robust to noises and changes in the illumination level, but it requires long computation time and large data storage for calculation. It needs large logic gates for implementation. It is difficult to apply in products that require real-time performance. In this paper, we propose the optimized Hough Transform circuit architecture and a lane departure warning system using vision device. We suggest the Hough Transform architecture to minimize the size of logic and the number of cycle time. Our implemented Hough Transform circuit show the good performance than other circuit architecture. We tested the Hough Transform circuit and lane departure warning system on the Xilinx FPGA board.
机译:本文介绍了具有优化霍夫变换电路的基于视觉的车道检测系统。 Hough变换是一种热门方法,可以找到图像中的线路功能。 这对噪声和照明级别的变化非常强大,但它需要长的计算时间和大数据存储来计算。 它需要大型逻辑门进行实施。 很难应用于需要实时性能的产品。 在本文中,我们提出了使用视觉装置的优化Hough变换电路架构和车道脱离警告系统。 我们建议Hough变换架构,以最大限度地减少逻辑的大小和循环时间的数量。 我们实施的Hough变换电路显示出比其他电路架构的良好性能。 我们在Xilinx FPGA板上测试了Hough变换电路和车道偏离警告系统。

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