Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Automated image processing technique for detecting and analysing concrete surface cracks
In the present work, an image processing technique that automatically detects and analyses cracks in the digital image of concrete surfaces is proposed. The image processing technique automates the measurement of crack characteristics including the width, length, orientation and crack pattern. In the proposed technique, a morphological technique was applied to correct the non-uniform brightness of the background, and enhanced binarisation and shape analysis were used to improve the detection performance; furthermore, detailed algorithms to calculate the crack width, length, orientation and an artificial neural network to recognise crack patterns including horizontal, vertical, diagonal (−45°), diagonal (+45°), and random cracks are proposed. An image processing program was developed for the proposed algorithm and a series of experimental and analytical investigations were performed to assess the validity of the algorithm. Then, the crack characteristics measured using the proposed technique were compared with those obtained using a conventional technique. The test results showed that the crack characteristics can be accurately measured and analysed using the proposed technique.
Automated image processing technique for detecting and analysing concrete surface cracks
In the present work, an image processing technique that automatically detects and analyses cracks in the digital image of concrete surfaces is proposed. The image processing technique automates the measurement of crack characteristics including the width, length, orientation and crack pattern. In the proposed technique, a morphological technique was applied to correct the non-uniform brightness of the background, and enhanced binarisation and shape analysis were used to improve the detection performance; furthermore, detailed algorithms to calculate the crack width, length, orientation and an artificial neural network to recognise crack patterns including horizontal, vertical, diagonal (−45°), diagonal (+45°), and random cracks are proposed. An image processing program was developed for the proposed algorithm and a series of experimental and analytical investigations were performed to assess the validity of the algorithm. Then, the crack characteristics measured using the proposed technique were compared with those obtained using a conventional technique. The test results showed that the crack characteristics can be accurately measured and analysed using the proposed technique.
Automated image processing technique for detecting and analysing concrete surface cracks
Lee, Bang Yeon (Autor:in) / Kim, Yun Yong (Autor:in) / Yi, Seong-Tae (Autor:in) / Kim, Jin-Keun (Autor:in)
Structure and Infrastructure Engineering ; 9 ; 567-577
01.06.2013
11 pages
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
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