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- RAILWAY TRACK CRACK DETECTION SYSTEM PROJECT PPT UPDATE
- RAILWAY TRACK CRACK DETECTION SYSTEM PROJECT PPT CODE
However, you have to modify and update parameters in Parameters.m, applicable to your own application. Run RunTrainClassifier.m and RunTest.m, consecutively.Manually annotate your object-of-interest using RunLabeling.m.Train your own classifier using your images You can also manually setup the path of "img" in Parameters.m. In the directory, you will have folders of "code","img" and "post". Download and unzip images and output data from the above link and allocate them in the same directory.
RAILWAY TRACK CRACK DETECTION SYSTEM PROJECT PPT CODE
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To address these limitations, a new vision-based visual inspection technique is proposed by automatically processing and analyzing a large volume of collected images from unspecified locations using computer vision algorithm. However, current procedures followed by human inspectors demand long inspection times to cover large and difficult to access bridges, and rely strongly on the inspector’s subjective or empirical knowledge. Visual inspection of civil infrastructure is customarily used to identify and evaluate faults such as cracks, corrosion, or deformation. Vision-Based Automated Crack Detection for Bridge Inspection