文章基本信息

标题：Application of neural network method for road crack detection
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作者：Yuslena Sari ; Puguh Budi Prakoso ; Andreyan Rizky Baskara 等
期刊名称：TELKOMNIKA (Telecommunication Computing Electronics and Control)
印刷版ISSN：2302-9293
出版年度：2020
卷号：18
期号：4
页码：1962-1967
DOI：10.12928/telkomnika.v18i4.14825
出版社：Universitas Ahmad Dahlan
摘要：The study presents a road pavement crack detection system by extracting picture features then classifying them based on image features. The applied feature extraction method is the gray level co-occurrence matrices (GLCM). This method employs two order measurements. The first order utilizes statistical calculations based on the pixel value of the original image alone, such as variance, and does not pay attention to the neighboring pixel relationship. In the second order, the relationship between the two pixel-pairs of the original image is taken into account. Inspired by the recent success in implementing Supervised Learning in computer vision, the applied method for classification is artificial neural network (ANN). Datasets, which are used for evaluation are collected from low-cost smart phones. The results show that feature extraction using GLCM can provide good accuracy that is equal to 90%.
关键词：ANN; GLCM; crack detection; feature extraction; image;