广西工学院学报2012，Vol.23Issue(3)：72-76,5.
一种快速的基于生物启发模型的路面裂缝特征提取与识别方法
A method for fast pavement cracking detection based on the biological inspired model
摘要
Abstract
Due to the complexity of shape and apparent differences of pavement cracks, it is difficult to characterize them with definite features. The wavelet, Gabor transform and its functions are usually predefined and cannot adapt to the characteristics of the pavement crack images. This paper proposes a novel joint maximization recognition algorithm in the resilient area, which is based on the characteristics of biologically inspired model (BIM). The algorithm uses the elastic neighborhood, the first adjacent neighbors domain or eight neighborhood image segmentation. Adaboost classifier is introduced in each region to select and retain key information, get rid of unwanted or negative information. Its eigenvectors can reflect the information in the original image comprehensively and its low computational complexity is helpful in real-time applications. The experimental results show that the overall recognition rate of the proposed method in pavement cracks is up to 99.13%, and its fast response time fully demonstrate the effectiveness of this method.关键词
生物启发模型/弹性邻域/特征提取Key words
bio-inspired model/flexibility neighborhood/feature extraction分类
信息技术与安全科学引用本文复制引用
徐奕奕,唐培和,倪志平..一种快速的基于生物启发模型的路面裂缝特征提取与识别方法[J].广西工学院学报,2012,23(3):72-76,5.基金项目
广西教育厅科研立项项目 （）
广西科技大学（筹）自然科学基金（校科自1261126）资助 （）
