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Implementation of lane detection system using optimized hough transform circuit

机译:利用优化的霍夫变换电路实现车道检测系统

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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:本文介绍了一种具有优化霍夫变换电路的基于视觉的车道检测系统。霍夫变换是一种在图像中查找线条特征的流行方法。这对于噪声和照明水平的变化非常强大,但是需要较长的计算时间和大量的数据存储才能进行计算。它需要大型逻辑门来实施。难以应用于需要实时性能的产品。在本文中,我们提出了优化的霍夫变换电路架构和使用视觉设备的车道偏离警告系统。我们建议使用霍夫变换(Hough Transform)架构,以最大程度地减少逻辑大小和循环时间。我们实现的霍夫变换电路显示出比其他电路体系结构更好的性能。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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