This thesis explores a novel approach to the computer vision eld in the form of lowcost computer vision intended for industrial use. The system proposed in this thesis, calledSimpleEye, is implemented and tested against an existing system. Dierent approachesto object detection and data extraction from a scene, as well as common applications ofcomputer vision in the industry, are examined. Three algorithms are implemented, aimedat dierent industrial applications. These are two types of object recognition, using CannyEdge detection and connected-component labeling, as well as barcode scanning. The tests,each targeting one of the implemented approaches, show promising results for low costcomputer vision. While the system is expectedly lacking in speed, it has no diculties inachieving good result in applications which are not highly time critical. SimpleEye yieldedaccuracy and precision comparable to commercial systems, with parts costing approximately100 USD. The tests show that the system is able to function in several computer visionapplications used today, including visual servoing, blob detection, blob tracking, and barcodescanning.
| Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:mdh-29363 |
| Date | January 2014 |
| Creators | Alnestig, Henrik |
| Publisher | Mälardalens högskola, Akademin för innovation, design och teknik |
| Source Sets | DiVA Archive at Upsalla University |
| Language | English |
| Detected Language | English |
| Type | Student thesis, info:eu-repo/semantics/bachelorThesis, text |
| Format | application/pdf |
| Rights | info:eu-repo/semantics/openAccess |
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