Identification of Crack Location to Aid Preventive Conservation of Timber-framed Buildings

Understanding the location of surface cracks relating to surrounding architectural and structural elements such as windows and columns is crucial for assessing the condition of buildings and implementing appropriate maintenance and repair strategies. Identifying crack location on exterior building walls is a systematic process of image acquisition, preprocessing, crack detection, and localization. This process is crucial for understanding deterioration mechanisms in aging structures and maintaining structural integrity. It reveals how loads and stresses are distributed, helping focus restoration efforts and preserve authenticity with minimal intervention. Current methods often fail to accurately locate cracks in heritage timber buildings, making it hard to assess their severity. This assessment is especially challenging due to the complex interaction between plaster and timber, and the unique way these structures distribute loads. The lack of advanced diagnostic tools for precise crack mapping and evaluation hampers efforts to effectively address structural vulnerabilities, posing risks to these culturally significant buildings' structural stability and historical authenticity. This study aims to identify crack locations in timber-framed buildings in relation to surrounding structural elements. The process begins with capturing high-resolution images of the building wall under good lighting followed by preprocessing these to enhance crack visibility through noise reduction, contrast, and edge enhancement. Cracks and architectural elements, such as windows and doors, are then identified using bounding boxes, and the distances between them are measured to analyze spatial relationships. The results are evaluated based on Loss Values and Average Precision metrics. Based on these results, the study supports improved structural diagnostics through image-based automation. This contributes to the fields of architecture, heritage conservation, structural assessment, and restoration planning by enabling more targeted and data-informed interventions. In doing so, it provides a foundation for advancing structural health monitoring and improving decision-making in heritage preservation practices.