000			01623nam a22001817a 4500
999			_c68372 _d68372
082			_aMG TH-0189 _bPRA
100			_aPrajapati, Jay (PG180370) _986455
245			_aRoad defect detection using high resolution imagery and computer vision (Softcopy is also available)
260			_c2020
300			_axv,46p.
505			_aTable of contents Certificate of Original Authorship i Certificate of Dissertation - Advisor’s consent iii Certificate of Dissertation - Program Chair v Acknowledgments vii Abstract ix List of figures xi List of tables xiv 1 Introduction1 1.1 Objective of the Study 1 1.2 Limitations 2 2 Literature Review3 2.1 Pavement Defects3 2.1.1 Cracking 3 2.2 Autonomous Surveillance Vehicle6 2.3 Stereo Vision8 2.3.1 Methodology 8 2.3.2 Epipolar Geometry 9 2.3.3 Stereo Image rectification 10 2.3.4 Correspondence problem 11 2.3.5 Depth Calculation 12 2.4 Computer Vision and Machine Learning 13 2.4.1 CNN in Deep Learning 14 2.4.2 What is ANN14 2.4.3 CNN18 3 Methodology20 4 Data Acquisition and Results 22 4.1 Equipment 22 4.2 Softwares Used 23 4.3 Equipment setup 24 4.3.1 Data collection 25 4.3.2 Calibration 25 4.3.3 Disparity map26 4.3.4 Object Recognition / Crack Detection27 4.4 Results 29 4.4.1 Drawbacks 30 4.5 Integration with GPS33 4.6 Study Area34 4.7 Drawbacks 37 4.8 Future Scope37 References xxxviii Appendix 1: Python Codes xl Plagiarism Report Copy 46
700			_aUpadhyay, Ashish (Guide) _986456
700			_aShahdadpuri, Suresh (Guide) _942050
890			_aIndia
891			_a2018 Batch
891			_aFT-PG
891			_aM.Sc. Geomatics