Title :
Asphalt surfaced pavement cracks detection based on histograms of oriented gradients
Author :
Kapela, Rafal ; Sniatala, Pawel ; Turkot, Adam ; Rybarczyk, Andrzej ; Pozarycki, Andrzej ; Rydzewski, Pawel ; Wyczalek, Michal ; Bloch, Adam
Author_Institution :
Comput. Eng., Poznan Univ. of Technol., Poznan, Poland
Abstract :
Cracks are the most requiring type of pavement distresses to detect and classify automatically. Due to its nature are easily absorbed by other types of pavement surface damages. Moreover, the diversity of pavement surface makes the image detection system requiring efficient computer algorithms. The paper presents the solutions tested on surface distress data which were collected automatically using downward facing cameras placed orthogonally to road pavement axis. Presented results focus on the crack-type pavement distresses. The achieved accuracy of the transverse, longitudinal and meshing cracks recognition based on the initial dataset prepared especially for this system, show it has very good chances to work efficiently with large image datasets collected during the inspection car runs.
Keywords :
asphalt; cameras; crack detection; image recognition; roads; structural engineering computing; surface cracks; asphalt surfaced pavement crack detection; automatic classification; automatic detection; computer algorithm; crack-type pavement distress; downward facing cameras; image datasets; image detection system; inspection car runs; longitudinal crack recognition; meshing crack recognition; oriented gradient histograms; pavement surface damages; pavement surface diversity; road pavement axis; surface distress data; transverse crack recognition; Histograms; Image edge detection; Noise; Optical surface waves; Roads; Surface cracks; Surface treatment; Histograms of Oriented Gradients; image processing; mesh cracking; pavement surface distress; single-type cracks detection;
Conference_Titel :
Mixed Design of Integrated Circuits & Systems (MIXDES), 2015 22nd International Conference
Conference_Location :
Torun
Print_ISBN :
978-8-3635-7806-0
DOI :
10.1109/MIXDES.2015.7208590