A new image processing strategy for surface crack identification in building structures under non‐uniform illumination. Issue 2 (5th October 2021)

• Record Type: Journal Article
• Authors: Parrany, Ahmad Mahdian; Mirzaei, Mohsen
• Is Part Of: IET image processing. Volume 16:Issue 2(2022)
• Page Start: 407
• Page End: 415
• Publication Date: 2021-10-05
• Subjects: Image processing -- Periodicals; 621.36705
• DOI: 10.1049/ipr2.12357
• Languages: English
• ISSNs: 1751-9659

Abstract

Abstract: Crack detection in building structures is an important approach to evaluating the safety of these structures. However, in some cases under special circumstances, it is very difficult to identify all features of cracks by visual inspection. To tackle this problem and offer a higher potential for practical implementations, developing an automatic crack detection method seems essential. This paper establishes a novel algorithm for surface crack detection in building walls based on image processing techniques to enhance crack visibility. One of the most prevalent issues in surface crack detection from digital crack images is non‐uniform illumination of background which makes narrow and tiny cracks indistinguishable. In this regard, an integrated approach, combining adaptive image threshold using local first‐order statistics, contrast‐limited adaptive histogram equalization, and noise filtering using non‐linear diffusion filtering, is proposed to extract the whole skeleton of the crack from digital crack images with non‐uniform illumination. Several realistic crack images, suffering from noise and uneven lighting of background, are processed through the proposed algorithm to demonstrate the robustness and high accuracy of the method.