Smart Image Processing Technology (SIPT)

State-of-the-Art Image Processing and Analysis

Images captured during the initial data acquisition / inspection phase are processed utilising SIAMA’s state-of-the-art Smart Image Processing Technology (SIPT). The process selects the appropriate image processing technique and defect mechanism required to detect, identify and analyse the defect type and determine the element condition state.

Six Key Steps for Image Analysis for Crack detection

1

Raw Image Acquisition

High resolution images of bridge elements are captured and used as raw data input for condition status analysis
2

Image Subtraction

Raw images are pre-processed using pixel subtraction techniques to balance images and reduce the effect of variable light exposure levels
3

Grey Scale Conversion

Colour images are digitally processed and converted to grey-scale intensity images
4

Threshold Segmentation

SIAMA’s thresholding image segmentation process is applied to create enhanced binary images
5

Cluster Detection / Classification

Statistical image analysis techniques identify pixel clusters and optimise analysis results
6

Damage Detection / Identification

Processed pixel clusters are categorised with respect to bridge defect type, condition and status

Enhanced Concrete Crack Detection

Below is a comparison of a manually obtained photograph showing a crack map on concrete and SIAMA's state-of-the-art computer evaluated crack pattern map.

How it works

In contrast, SIAMA’s computer-evaluated crack pattern map incorporates image processing technology to highlight all detected cracks and identify maximum crack width and location.

SIAMA’s data analysis and management software package, Smart Infrastructure Management System (SIMS) Bridges utilises the bridge component condition rating data outputs of SIAMA’s Smart Image Processing Technology (SIPT) module, to conduct current and future bridge performance analysis at a component, project and network level.

Typical Crack Pattern Map crack
SIAMA's Computer Analysed Crack Pattern Map

Features and benefits

  • SIAMA’s image processing technology provides full objective data utilising sub-millimetre accurate images;
  • SIAMA’s image processing software recognises 14 different types of surface defect;
  • SIAMA’s image processing technology provides an overall condition rating for each individual bridge component and the entire structure; and
  • SIAMA’s image processing software can be customised to suit a variety of alternate structural condition evaluations.

For more information contact SIAMA

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