Open Access Open Access  Restricted Access Subscription or Fee Access

Leakage Detection on Building Façade using Thermal Image

A. Jasmine Bagban, V.B. Baru


The goal of this research is to detect leakage on building facade using thermal image. Defining regions of interest precisely is one of the important problems in thermal image processing. Once the boundaries of the investigated objects are calculated, thermal parameters, such as average temperature, standard deviation, histograms, etc. can be easily obtained. The main aim is to find image features that describe leakage of building facade thermographs and to use these parameters to classify thermal image of building facade with and without leakage. Feature extraction from image and feature matching with stored features in feature vector are two key steps to find out leakage on building facade automatically. There are many different methods that describe image features. The basic feature consider is the edge, Detection of edge is a terminology in image processing and computer vision particularly in the areas of feature detection and extraction to refer to the algorithms which aims at identifying points in a digital image at which the image brightness changes sharply or more formally has discontinuities. The need of edge detection is to find the discontinuities in depth, discontinuities in surface orientation, changes in material properties and variations in scene illumination. In this, a new edge extraction approach is presented, which is consisted of Canny edge detector. Secondly, there are large group of methods which are based on statistical parameters calculations. Parameters like mean value, standard deviation, skewness, kurtosis, energy, entropy etc. can be used to compare thermal images. Statistical features are calculated by using simple image processing techniques. Lastly region properties of an image such as area, centroids, and perimeters are considered. Based on the values of these features of a digital thermal image, we have made an attempt to classify the image in to two basic categories like normal image without leakage and defective image with leakage.


Edge Detection, First Order Statistics Method, Image Processing, Thermal Images

Full Text:



Slobodan Ribaric, Darijan Marcetic, Denis Stjepan Vedrina, “A knowledge-based system for the non-destructive diagnostics of façade isolation using the information fusion of visual and IR images”, Expert Systems with Applications 36 (2009) 3812–3823

Y.Ramadevi, T.Sridevi, B.Poornima, B.Kalyani,“ segmentation and object recognition using edge detection techniques”, International Journal of Computer Science & Information Technology (IJCSIT), Vol 2, No 6, December 2010

Beant Kaur, Gurdeep Mohal, Palak Gupta, Jasleen kaur, “Mathematical Morphological Edge Detection for Different Applications :A Comparative Study”, IJCST Vol. 2, Issue 2, June 2011 ,ISSN : 2229 - 4333

Y. David Solomon Raju, D. Krishna Reddy“ Digital Image Processing Techniques Based on Edge Feature Extraction”, International Journal of Advanced Engineering & Application, Jan 2011 Issue.

Holalu Seenappa Sheshadri and Arumugam Kandaswamy, “Breast tissue classification using statistical feature extraction of mammograms”, Vol.23 No.3,2007

Oky Dwi Nurhayati, Dr. Adhi Susanto, Dr. Thomas Sri Widodo, Dr. Maesadji Tjokronagoro, “Principal Component Analysis combined with First Order Statistical Method for Breast Thermal Images Classification”, IJCST Vol. 2, Issue 2, June 2011 ISSN : 2229 - 4333

Dr. H.B.Kekre, Sudeep D. Thepade, Tanuja K. Sarode and Vashali Suryawanshi,“ Image Retrieval using Texture Features extracted from GLCM, LBG and KPE”, International Journal of Computer Theory and Engineering, Vol. 2, No. 5, October, 2010

Sanjay B. Patil, Dr. Shrikant K. Bodhe, “image processing method to measure sugarcane leaf area”, International Journal on Computer Science and Engineering (IJCSE), ISSN : 0975-5462 Vol. 3 No. 8 August 2011

Sanjay B. Patil, Dr. Shrikant K. Bodhe, “Betel Leaf Area Measurement Using Image Processing”, International Journal on Computer Science and Engineering (IJCSE), ISSN : 0975-3397 Vol. 3 No. 7 July 2011

Devendra Singh Raghuvanshi, Dheeraj Agrawal, “ Human Face Detection by using Skin Color Segmentation, Face Features and Regions Properties”, International Journal of Computer Applications (0975 – 8887) Volume 38– No.9, January 2012.

Ayse Tavukcuoglua, Arda Duzgunesa, Sahinde Demircib, Emine N. Caner-Saltıka, “The assessment of a roof drainage system for an historical building”, Building and Environment 42 (2007) 2699–2709

Tavukcuoglua, A. Duzgunes¸b, E.N. Caner-Saltıkc,S¸ Demircid, “Use of IR thermography for the assessment of surface-water drainage problems

in a historical building, Agzıkarahan (Aksaray), Turkey”, NDT&E International 38 (2005) 402–410

Ocana et al. “ Thermographic survey of two rural buildings in Spain”, Energy and Buildings 36 (2004) 515–523

C.A.Balaras and A.A.Argiriou ,“Infrared thermography for building diagnostics”, Energy and Buildings 34 (2002) 171–183

D.J. Titman, “Applications of thermography in non-destructive testing of structures”, NDT&E International 34 (2001) 149–154

R. Gonzalez and R. Woods, Digital image processing, 2nd ed., PrenticeHall, 2001

Web Site – www.


  • There are currently no refbacks.

Creative Commons License
This work is licensed under a Creative Commons Attribution 3.0 License.