摘要
应用基于小波变换的图像分解和重构方案可以进行公路路面裂缝的检测与识别。首先对路面图像进行多分辨二维离散小波分解,根据在每个尺度2j上小波系数模最大值和相位(梯度方向)这两个分量的大小确定边缘的位置,进一步变换小波分解系数,达到去除噪音,加强裂缝边缘的效果。并通过实验分析和讨论了不同的小波基、不同分辨率水平、重构中使用的分解子图像对路面图像裂缝分割的影响,最后用简单的阈值技术生成二值图像,把裂缝从背景图像中分离出来。
The image decomposition and reconstruction programs based on wavelet transform are applied to the detection and recognition of pavement cracking. Firstly, 2-D discrete wavelet multi-resolution decomposition is carries out on the im- age of the pavement. The location of the edge is determined by the size of two components, that is, the phase ( gradient di- rection ) and local modulus maxima of the wavelet transform at different decomposition levels. The wavelet decomposition co- efficients are further transformed to remove noises and to enhance the edges of cracks. Then, effects of different wavelet ba- ses, different multi-resolution levels, the decomposed sub-images used in reconstruction on the segment of pavement image cracks are discussed and analyzed through experiments. Finally, simple threshold technology is used to generate binary im- age, which can discriminate cracks against background regions in the reconstructed images.
出处
《重庆交通大学学报(自然科学版)》
CAS
北大核心
2010年第1期69-72,共4页
Journal of Chongqing Jiaotong University(Natural Science)
基金
交通运输部西部交通建设科技项目(200431800054)
四川省交通科技项目(SC200600382C)
关键词
道路工程
裂缝识别
小波变换
路面裂缝
图像重构
图像分割
road engineering
cracking recognition
wavelet transform
pavement cracking
image reconstruction
image segmentation