Proceedings Article | 9 May 2024
KEYWORDS: Cameras, Image processing, Aerial cameras, Algorithm development, Civil engineering, Computer vision technology, Buildings, C++, Inspection, Signal processing
Computer vision and signal processing techniques have been adopted in several areas of human knowledge. Usually, these techniques are applied to the extraction of information from images, in order to reduce common errors inherent in repetitive work and reduce production times. In industry, signal processing is used to inspect the quality of products, checking their irregularities and whether they are within acceptable tolerances, in accordance with quality standards. In civil construction pattern tracing and image processing is used with little or no frequency to monitor civil engineering structures. Applications of intelligent sensory systems and intelligent structures that enable traceability by image are the great technological innovation implemented in this study in the field of civil engineering. Wall cracks, fissures and other types of changes are pathological manifestations of buildings observed in masonry, beams, pillars, slabs, floors and other elements, usually caused by tensions in the materials. If the materials are requested with an effort greater than their resistance, failure occurs causing an opening, and according to their thickness it will be classified as Cracks or fissures. Among the various ways to acquire images in buildings is the use of Drones that use different cameras for image acquisition. The use of a camera coupled to the Drone has been an alternative to track objects and places that are difficult to access, in the case of bridges, buildings and viaducts, where there is a need for observation in loco, the use of these devices facilitates the verification of restricted and difficult areas access. In this study, the Pixy camera was selected in order to verify its versatility in capturing artificial images that simulate cracks and fissures. The adopted experimental method consisted of image capture using the Pixy camera coupled to the Drone in a controlled laboratory environment. After capturing the image, an algorithm programmed in C++ language with data correlation capability was used to identify the type of cracks and fissures. The main result obtained from the research identified that there is a distance of 30 cm that corresponds to the approximation limit of the Drone with the Pixy camera of the civil engineering structures to be analyzed. The algorithm developed in C++ language to program the Pixy camera enabled remote sensing and traceability of patterns of cracks and fissures in civil engineering structures, with an accuracy of 99.99%, a result that corroborates the efficiency of the research method adopted.
