Mahmoud R. Halfawy

Efficient Algorithm for Crack Detection in Sewer Images from Closed-Circuit Television Inspections

AbstractThis paper presents a new algorithm for automated crack detection in sewer inspection closed-circuit television (CCTV) images. Cracks often have a long and thin rectangular shape with a darker appearance relative to other components in the image; therefore, they typically manifest as edges. The proposed algorithm exploits previous information on the visual characteristics of crack features in typical CCTV images to efficiently identify actual cracks and filter out background noise. The algorithm consists of three main steps. The first preprocessing step prepares the CCTV image for crack detection by identifying a set of candidate crack fragments using the Sobel method to detect horizontal and vertical edges separately. The Hough transform is then used to identify and remove the edges associated with information labels typically found in CCTV images. The second step applies a set of morphological operations to enhance candidate crack segments by filling the gaps between closely adjacent and aligned...

Video Processing Techniques for Assisted CCTV Inspection and Condition Rating of Sewers

This chapter describes the development of a software system to semi-automatically extract historical condition data information from archived sewer inspection …

Integrated Vision-Based System for Automated Defect Detection in Sewer Closed Circuit Television Inspection Videos

AbstractThis paper discusses the development of a general framework and software system to support automated analysis of sewer inspection closed-circuit television (CCTV) videos. The proposed system aims primarily to support the off-site review and quality control process of the videos and to enable efficient reevaluation of archived CCTV videos to extract historical sewer condition data. Automated analysis of sewer CCTV videos poses several challenges including the nonuniformity of camera motion and illumination conditions inside the sewer. The paper presents a novel algorithm for optical flow-based camera motion tracking to automatically identify, locate, and extract a limited set of video segments, called regions of interest (ROI), that likely include defects, thus reducing the time and computational requirements needed for video processing. The proposed algorithm attempts to recover the operator actions during the inspection session, which would enable determining the location and relative severity of...

A Simulation Study on Using Inverse Transient Analysis for Leak Detection in Water Distribution Networks

Inverse transient analysis, developed by several researchers in recent years as a promising and low-cost leak detection technique, has been successfully demons…

A Multi-Objective Optimization Decision Support Model for Renewal Planning of Sewer Networks

A new integrated approach for optimal renewal planning of municipal infrastructure systems has been developed. This chapter discusses the application of the proposed approach to implement a GIS-based Decision Support System (DSS) to support the renewal planning of sewer networks. The approach involves several steps addressing condition rating, risk assessment, and prioritization of sewers. It also incorporates a procedure for identifying and selecting the most suitable renewal technologies. A genetic algorithm (GA)-based multi-objective optimization (MOO) technique is used to find a Pareto front and identify a set of feasible solutions, in which a set of sewers is selected for renewal each year, along with the associated costs and expected benefits in terms of condition improvement and risk reduction. The chapter also presents an example application of the prototype DSS on the sewer network in Regina, Canada.

Closure to “Integrated Decision Support System for Optimal Renewal Planning of Sewer Networks” by M. R. Halfawy, L. Dridi, and S. Baker

The authors of this paper discussed a number of issues in wastewater infrastructure management, including condition rating, deterioration modeling, risk assessment, asset prioritization, and optimization of rehabilitation strategies within budgetary constraints. While their effort is certainly laudable, I want to offer some comments about the deterioration modeling as presented in the “Example System Use” on p. 368, as well as discussed elsewhere in the paper. The authors recognize the importance of quality and quantity of condition assessment data to develop reliable deterioration models for sewer networks, but they fall short on the importance of using appropriate and correct model development and validation procedures. For example, the paper suggests and applies ordinary regression model s for deterioration of wastewater pipelines. However, it may not be advisable, and be “theoretically inappropriate” Lynch 2007 to use ordinary regression model s to predict discrete and ordered outcomes for the following reasons: 1. The deterioration may be intrinsically continuous, but it is usually measured in discrete and ordinal i.e., noncontinuous ways, in terms of, for example, structural internal condition grades ICGs or structural performance grades SPGs for wastewater pipelines. As noted by the authors, the Water Research Center’s Sewerage Rehabilitation Manual suggests