Two‐dimensional DFT with sliding and hopping windows for edge map generation of road images

Abstract

An edge map generation technique based on two-dimensional discrete Fourier transform with sliding and hopping windows is proposed for road images to detect the lanes and road markings. A 2 × $\times$ 2 sliding/hopping window DFT with bin indices ( k 1 , k 2 = 0 , 1 $k_1, k_2 = 0,1$ ) for horizontal edge detection and ( k 1 , k 2 = 1 , 0 $k_1, k_2 = 1,0$ ) for vertical edge detection has been proposed. The 2-D SDFT/HDFT-based edge detector has been proved to be more efficient for lane and road marking images in comparison with conventional edge detectors and cellular neural network based edge detectors. In the presence of noise and various signal to noise ratio conditions, the horizontal and vertical edges have been efficiently recovered with good Pratt figure of merit without applying any pre-processing, noise removal process, and post processing techniques. The PFOM was found to be quite stable with wide threshold range for various noise levels. The consistent performance of the proposed edge detector is proved with MSE and PSNR determination of detected edge images. Moreover, the proposed 2-D SDFT/HDFT-based edge detector performs well in developing edge maps for real-time road videos. The system-on-chip implementation of the 2-D SDFT/HDFT edge detector on Cyclone IV FPGA chip is also carried out for detecting the lane and road markings.