Quality analysis using three-dimensional modelling and image processing techniques

Purpose

This paper aims to propose a system for defect detection in constructed elements that is able to indicate deformity positions. It also evaluates the defects in finishing materials of constructed building elements to support the subjective visual quality investigation of the aesthetics of an architectural work.

Design/methodology/approach

This strategy depends on defect features analysis that evaluates the defect value in digital images using digital image processing methods. The research uses the three-dimensional (3D) modeling techniques and image processing algorithms to generate a system that is able to perform some of the monitoring activities by computers. Based on the collected site scans, a 3D model is created for the building. Then, several images can be exported from the 3D model to investigate a specific element. Different image denoizing techniques are compared such as mean filter, median filter, Wiener filter and Split–Bregman iterations. The most efficient technique is implemented in the system. Then, the following six different methods are used for image segmentation to separate the concerned object from the background; color segmentation, region growing segmentation, histogram segmentation, local standard deviation segmentation, adaptive threshold segmentation and mean-shift cluster segmentation.

Findings

The proposed system is able to detect the cracks and defected areas in finishing works and calculate the percentage of the defected area compared to the total captured area in the photo with high accuracy.

Originality/value

The proposed system increases the precision of decision-making by decreasing the contribution of human subjective judgment. Investigation of different finishing surfaces is applied to validate the proposed system.