为了提高图像处理中线段的检测精度和速度,提出一种称为“合击-分进( UND)”的精确且快速的线段检测方法。该方法包括频域的频谱合并和Radon空间的正弦图分解两个阶段。在合击阶段,原始图像经过二维并行多层傅里叶变换、直角坐标至极坐标映射、一维傅里叶逆变换等处理后得到它的正弦图;在分进阶段,检测Radon空间正弦图的各个峰值及其邻域内的蝶翼边缘,每一邻域对应图像空间中的一个窗口,并针对每个窗口正弦图的蝶型曲线进行边缘分析,从而得到线段的端点。实验结果表明:UND方法在分割精度上优于SHT、RHT和LSD等经典线段分割方法,检测速度上优于SHT和LSD方法。 UND算法不但能提高准确度,还能降低计算成本,增强对噪音干扰的鲁棒性。
A fast line segment detection method, unite-and-divide ( UND) approach, is investigated, which includes two phases, namely the union of spectra in the frequency domain and the division of the sinogram in Radon space respectively. In the union phase, for a given image, its sinogram is obtained by parallel 2D multilayer Fourier transform, Cartesian-to-polar mapping and 1D inverse Fourier transform. In the division phase, every peaks and edges of butterfly wings in its neighborhood in sinogram are firstly specified, with each neighborhood area corresponding to a window in image space, and then, by applying edge-analyzing to each sinogram of each windowed separately, the endpoints of line segments are extracted. Our experiments are conducted on benchmark images, the results reveal that the UND method yields high accuracy, low computational cost and is more robust to noise.