IJIRST (International Journal for Innovative Research in Science & Technology)ISSN (online) : 2349-6010

 International Journal for Innovative Research in Science & Technology

Efficient Road Patch Detection based on Active Contour Segmentation


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International Journal for Innovative Research in Science & Technology
Volume 3 Issue - 4
Year of Publication : 2016
Authors : Ajeesha A A ; Arun Kumar M N

BibTeX:

@article{IJIRSTV3I4025,
     title={Efficient Road Patch Detection based on Active Contour Segmentation},
     author={Ajeesha A A and Arun Kumar M N },
     journal={International Journal for Innovative Research in Science & Technology},
     volume={3},
     number={4},
     pages={166--173},
     year={},
     url={http://www.ijirst.org/articles/IJIRSTV3I4025.pdf},
     publisher={IJIRST (International Journal for Innovative Research in Science & Technology)},
}



Abstract:

Pavement management systems for monitoring the road surface distress rely on upto date road condition data to provide effective decision support for scheduling the road maintenance. The recent method includes subjective laborious and time-consuming surveys. Even though specialized vehicles equipped with additional sensors exist to automatically collect the data, their high cost restricts their usage to the primary road network and hence this leads to long gaps between inspections. Therefore, a pavement surface condition monitoring systems that provide inexpensive and frequent updates on the road condition are needed. Such systems would require robust and automatic defect detection methods using low cost sensors. So a novel method is proposed for detecting the road patches from the image and video data collected based on active contour segmentation. The visual characteristics used to detect the patch consist of: 1) patch consists of a closed contour and 2) texture of patch is same as with the surrounding intact pavement. The patch is correctly segmented using active contour which accurately detect the total number of patches, its area and shape and hence reduces some false positives. In order to trace the patch in subsequent video frames, it is then passed to kernel tracker. This way redetection of patch is avoided and each patch is reported only once. The process is implemented in a MATLAB 2014prototype and tested with video data collected from local roads in Ernakulam, India. The results show that the suggested method has 82.75% precision and 92.31% recall and 80% accuracy for detecting the patches in road images.


Keywords:

Active Contour Segmentation, Automatic Detection, Image Processing, Patch, Pavement Defect


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