IR Building Analysis with Extraction of Elements Using Image Segmentation and RetinaNet

Thermography is being increasingly used in building inspection due to its capability determine various defects, as this enables the development of improvement strategies for efficient energy consumption. In paper, AI algorithms are combined, and new segmentation proposed improve accuracy insulation assessments. Paired visual IR pictures taken from same angle complementarily feed different sequential neural networks employed extract characteristic segments buildings. The optical images contain information required identify separate objects, such windows, doors, walls. assessment. This an automated analysis a large number objects within assessment with respect proper viewing resolution. Variations measured temperatures segmented regions estimated by referring their representations frames, which allows general conclusions concerning state be drawn, using trained network, heat losses localized frames. output levels consecutive frames compared effects on object representation recording aspects.