DocumentCode :
596613
Title :
Crack detection in concrete surfaces using image processing, fuzzy logic, and neural networks
Author :
Choudhary, Girish Kumar ; Dey, Shuvashis
Author_Institution :
Dept. of Civil Eng., Indian Inst. of Technol.-Kharagpur, Kharagpur, India
fYear :
2012
fDate :
18-20 Oct. 2012
Firstpage :
404
Lastpage :
411
Abstract :
Automation in structural health monitoring has generated a lot of interest in recent years, especially with the introduction of cheap digital cameras. This paper presents fuzzy logic and artificial neural network based models for accurate crack detection on concrete. Features are extracted from digital images of concrete surfaces using image processing which incorporates the edge detection technique. The properties of extracted features are fed into the models for detecting cracks. Two kinds of approaches have been implemented in this study: the image approach which classifies an image as a whole, and the object approach which classifies each component or object in an image into cracks and noise. The models have been tested on 205 images and evaluated on the basis of five measures of performance.
Keywords :
automatic optical inspection; concrete; condition monitoring; crack detection; edge detection; feature extraction; fuzzy logic; image classification; neural nets; structural engineering computing; artificial neural network; concrete surfaces; crack detection; digital cameras; digital images; edge detection technique; feature extraction; fuzzy logic; image classification; image processing; object classification; structural health monitoring automation; Accuracy; Concrete; Fuzzy logic; Image edge detection; Neural networks; Noise;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Advanced Computational Intelligence (ICACI), 2012 IEEE Fifth International Conference on
Conference_Location :
Nanjing
Print_ISBN :
978-1-4673-1743-6
Type :
conf
DOI :
10.1109/ICACI.2012.6463195
Filename :
6463195
Link To Document :
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