Texture Analysis Based Damage Detection of Ageing Infrastructural Elements

摘要: :  To make visual data a part of quantitative assessment for infrastructure maintenance management, it is important to develop computer-aided methods that demonstrate efficient performance in the presence variability damage forms, lighting conditions, viewing angles, and image resolutions taking into account luminous chromatic complexities data. This article presents semi-automatic, enhanced texture segmentation approach detect classify surface on elements successfully applies them range images damage. The involves statistical analysis spatially neighboring pixels various color spaces by defining feature vector includes measures related pixel intensity values over specified statistics derived from Grey Level Co-occurrence Matrix calculated quantized grey-level scale. Parameter optimized non-linear Support Vector Machines are used vector. A Custom-Weighted Iterative model 4-Dimensional Input Space introduced. Receiver Operating Characteristics employed assess enhance detection efficiency under conditions.