Determination of Thermal Bridge of the Buildings from Infrared Images

被引:0
作者
Bettemir, Onder Halis [1 ]
机构
[1] Inonu Univ, Muhendislik Fak, Insaat Muh Bolumu, Malatya, Turkiye
来源
JOURNAL OF POLYTECHNIC-POLITEKNIK DERGISI | 2024年 / 27卷 / 03期
关键词
Edge detection; binarization; otsu algorithm; EDGE-DETECTION; CHARACTER-RECOGNITION; BOUNDARY DETECTION; BINARIZATION; THERMOGRAPHY; DESIGN; HOUSES; SOBEL;
D O I
10.2339/politeknik.1144858
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Vast majority of the existing buildings in Turkiye are not inspected for thermal insulation quality during the construction process therefore, thermal insulation performance of the existing buildings cannot be known. Measuring the thermal insulation performance of the buildings by scraping the plaster and examining the heat insulation material is not a viable solution when the size of the building stock of Turkiye is considered. In this study, detection of thermal bridges of the buildings by processing the thermal images of the buildings is proposed. The method is based on the binarization of the thermal image by the classification of the building elements as heat loss element or no heat loss element by analyzing the thermal image of the building. Global threshold methods and adaptive local threshold methods applied for binarization. All of the implemented methods require a threshold value for the classification. Determining a valid threshold value for all images is not possible therefore the threshold value is determined by the Otsu algorithm. Threshold determination process is executed both on the thermal image and the edge image. Obtained threshold values are implemented on the thermal images and the edge images. Local edge detection algorithms derived from the literature are compared by examining five thermal images and the comparison revealed that the Modified II Frei-Chen and Second-order Laplace operator provided the most suitable result. The case studies revealed that the thermal insulation performance of the existing building stock can be determined quickly, economically and reliably by implementing the proposed method.
引用
收藏
页数:36
相关论文
共 74 条
[1]   QUANTITATIVE DESIGN AND EVALUATION OF ENHANCEMENT-THRESHOLDING EDGE DETECTORS [J].
ABDOU, IE ;
PRATT, WK .
PROCEEDINGS OF THE IEEE, 1979, 67 (05) :753-763
[2]   An Instance Segmentation and Clustering Model for Energy Audit Assessments in Built Environments: A Multi-Stage Approach [J].
Arjoune, Youness ;
Peri, Sai ;
Sugunaraj, Niroop ;
Biswas, Avhishek ;
Sadhukhan, Debanjan ;
Ranganathan, Prakash .
SENSORS, 2021, 21 (13)
[3]   Automatic recognition of handwritten Arabic characters: a comprehensive review [J].
Balaha, Hossam Magdy ;
Ali, Hesham Arafat ;
Badawy, Mahmoud .
NEURAL COMPUTING & APPLICATIONS, 2021, 33 (07) :3011-3034
[4]  
Bayram F., 2020, J POLYTECH, V23, P955
[5]  
Bettemir O.H., 2020, ANATOLIAN J COMPUTER, V5, P22
[6]   GiB: A Game Theory Inspired Binarization Technique for Degraded Document Images [J].
Bhowmik, Showmik ;
Sarkar, Ram ;
Das, Bishwadeep ;
Doermann, David .
IEEE TRANSACTIONS ON IMAGE PROCESSING, 2019, 28 (03) :1443-1455
[7]  
Bostanci L., POLITEKNIK DERGISI, V25, P75
[8]  
Bradley Derek, 2007, Journal of Graphics Tools, V12, P13
[9]   Adaptive Digital Hologram Binarization Method Based on Local Thresholding, Block Division and Error Diffusion [J].
Cheremkhin, Pavel A. ;
Kurbatova, Ekaterina A. ;
Evtikhiev, Nikolay N. ;
Krasnov, Vitaly V. ;
Rodin, Vladislav G. ;
Starikov, Rostislav S. .
JOURNAL OF IMAGING, 2022, 8 (02)
[10]   Comparative appraisal of global and local thresholding methods for binarisation of off-axis digital holograms [J].
Cheremkhin, Pavel A. ;
Kurbatova, Ekaterina A. .
OPTICS AND LASERS IN ENGINEERING, 2019, 115 :119-130