Image Processing For Construction Equipment Idle Time Analysis

Abstract

Accurate analyses of equipment idle time is crucial for the efficient utilization of construction equipment in a large construction project. The less idle time the equipment has, the higher productivity the construction can achieve. However, it is not practical to measure construction equipment idle time by human visual observation. This paper describes an image processing-based methodology to automatically quantify the idle time of construction equipment. The image color space, HSV (Hues, Saturations, and Values), is used as the basis for image segmentation and tracing algorithms. The HSV color space shows significant advantages over the RGB (Red, Green, and Blue) color space in identifying and tracing construction equipment. The centroid coordinates of equipment are used as the indicators of movement. Experimental results show that the proposed methodology has a promising potential for effective equipment management in construction projects.

Infrared thermography for a quick construction progress monitoring approach in concrete structures

“…Neto et al [31] have proposed a colour-edge-detector algorithm to identify the construction components, in which a predefined library based on the RGB ranges for different materials is created. Zou and Kim [32] have developed a method based on HSV (hue, saturation, and value) and colour to compute the idle time of hydraulic excavators automatically. Golparvar-Fard et al [14] have proposed an image-based approach to estimate project status information using daily photographs captured from a construction site.…”

An automated system for the creation of an urban infrastructure 3D model using image processing techniques

“…Zou and Kim (2007) and Wu et al (2010) used digital imaging to monitor construction processes, while Konkol and Prokopski (2007) and Regez et al (2008) relied on digital imaging for structural analyses. Image-based 3D modeling methodologies have been used for the digital documentation of historical buildings (Styliadis, 2007) and historical caravansaries (Yilmaz et al, 2008).…”

“…Red, Green, and Blue (RGB), Hue, Saturation, and Value (HSV), and Luminosity, Chroma, and Hue (LCH) are some examples of color space. A previous study (Zou and Kim, 2007) shows that HSV color space can provide a stable platform such that objects of interest exposed in an outdoor environment can successfully be separated from the background region. We tested a sample image of a traffic sign to investigate the feasibility of HSV-based thresholds (Fig.…”

Bridge Construction Progress Monitoring Using Image Analysis

“…Zou and Kim (2007) suggested a strategy for analyzing idle time of hydraulic excavators, using the hue, saturation, and value color space. Quiñones-Rozo et al (2008) applied image processing techniques for identifying and quantifying the excavating area.…”