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Tesi etd-05172019-190849


Thesis type
Tesi di laurea magistrale
Author
FARNESI, CHIARA
URN
etd-05172019-190849
Title
Experimental Design and Development of an Embedded Computer Vision System for Detection and Analysis of Pantographs
Struttura
INGEGNERIA DELL'INFORMAZIONE
Corso di studi
EMBEDDED COMPUTING SYSTEMS
Commissione
relatore Prof. Avizzano, Carlo Alberto
correlatore Ing. Pampana, Matteo
correlatore Ing. Tripicchio, Paolo
Parole chiave
  • head pose
  • pantograph detection
  • ORB
  • template matching
  • machine learning
  • HAAR
  • HOG
  • Computer Vision techniques
Data inizio appello
21/06/2019;
Consultabilità
parziale
Data di rilascio
21/06/2089
Riassunto analitico
Design and development of a vision system for detection and analysis of the pantograph head.
The proposed architecture detects, tracks, and analyzes the position of the pantograph head
and its geometrical structure to identify possible sources of defects that could be risky for train circulation.

The system records images, localizes relevant frames, compensates images color. Then, for the relevant images, the system detects the position and the spatial orientation of the pantograph head. Particular care has been posed to achieve precise shape and localization of the head. I developed a new processing pipeline that sequentially improves position accuracy. The pipeline exploits Computer Vision techniques such as template matching; machine learning (through HAAR cascade recognition and HOG objects detection; key features detection (SIFT and ORB algorithms); foreground extraction (GrabCut); color filtering with edge preservation; lines detection (Hough Transform).

Several parameters have optimized through relevant comparative analyses that address the accuracy of the final result and robustness of detection. Experimental results have been compared with a ground-truth composed of field data acquisition and result labeled by humans.
The achieved results demonstrated the capability of the system for being used as a decision support system in maintenance activities.
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