| Popis: |
Cracks in concrete structures can be formed due to many reasons such as physical damage, hydraulic shrinkage, thermal shrinkage, swelling, and corrosion of steel reinforcements. These vulnerable entities present in structures are responsible for reducing the performance and strength of the concrete. Inspecting these entities and deciding the nature of these cracks is an essential element for the maintenance of the structure. Concrete crack detection based on Image Processing and Artificial Intelligence involves using computer vision techniques to automatically identify and classify cracks in concrete structures. Detection and classification of these cracks can be done using a combination of various machine learning algorithms and image processing techniques. Our project aims to detect the location of the cracks on the structures using various processing techniques such as resizing, gray scaling, binarization, segmentation, enhancement, and filtering out the noise. Detection of the cracks can be performed using thresholding techniques. Later classification of these detected cracks can be done using Deep Learning techniques concerning various deciding parameters such as length, width, and area of cross-section of the detected crack. The cracks can be classified based on their size they can be thin, medium, or wide cracks. They can also be classified based on the appearance of the crack, which may be longitudinal, vertical or transversal. |
