Mechanical & Materials Engineering Research Collection
Permanent URI for this collection
For more information, please visit the official web page.
Browse
Browsing Mechanical & Materials Engineering Research Collection by Subject "4-Dimensional Input Space model"
Now showing 1 - 1 of 1
Results Per Page
Sort Options
- PublicationTexture Analysis Based Damage Detection of Ageing Infrastructural Elements(Wiley Online Library, 2012-11-08)
; ; ; 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 of variability in damage forms, lighting conditions, viewing angles, and image resolutions taking into account the luminous and chromatic complexities of visual data. This article presents a semi-automatic, enhanced texture segmentation approach to detect and classify surface damage on infrastructure elements and successfully applies them to a range of images of surface damage. The approach involves statistical analysis of spatially neighboring pixels in various color spaces by defining a feature vector that includes measures related to pixel intensity values over a specified color range and statistics derived from the Grey Level Co-occurrence Matrix calculated on a quantized grey-level scale. Parameter optimized non-linear Support Vector Machines are used to classify the feature vector. A Custom-Weighted Iterative model and a 4-Dimensional Input Space model are introduced. Receiver Operating Characteristics are employed to assess and enhance the detection efficiency under various damage conditions.Scopus© Citations 99 608