Aine tutvustab meetodeid, millega intellektuaalseid masinanägemissüsteeme saab konstrueerida ja mida kasutada praktilistes rakendustes. See aine hõlmab tarkvara, riistvara ja kujutiste saamise meetodeid.

Machine vision is the study of methods and techniques whereby artificial vision systems can be constructed and usefully employed in practical applications. It includes the software, the hardware environment and image acquisition techniques.

Üliõpilane teab riistvara keskkonda ja kujutise saamise meetodeid ning vahendeid. Oskab kasutada arukate masinanägemissüsteemide meetodeid ja tehnikaid praktilistes rakendustes.

Student must know: the hardware environment and image acquisition techniques.
The student should be able to: apply the methods and techniques of artificial vision systems in practical applications.

Eri tüüpi visuaalandurid. Videokaamerate ehitus ja tööpõhimõtted. Kujutise ja videovoolu import ja eksport. Kujutise ja videovool standardseadmetest. Konkreetsete esemete tuvastamine ja jälgimine. Kujutiste ja videovoolude haaramine snap reaalsetesse stsenaariumitesse. Videovoolu töötlemine. Video vahekontroll algoritmides. Algoritmide testimine eri tingimustes. Rakendamine: esemete olemasolu/puudumise avastamine; pindala veebikontroll, transpordi tuvastamine, ruumilise asukoha määramine; eri koodide (vöötkoodid, 2D-koodid) tuvastamine; biomeetrilised mõõtmised.

Different types of visual sensors. Videocameras. Import and export of images and video streams. The images and video streams capture from standard devices for imaging. The detection and tracking of the specific objects. The pictures and video snap to the real scene. Processing of the video streams. Check the intermediate video inside of the algorithms.The algorithms testing in a wide range of conditions. Application: Presence/Absence detection; Web surface inspection; determination of the spatial location; the objects various physical parameters measurement, transport monitoring; identification of the various codes (bar codes, 2D-codes); detection and face recognition.

vt fail

see attachment

Iseseisva töö orienteeruvaks mahuks eeldatakse 32 tundi. Sellest 16 tundi on mõeldud aine teoreetilise osa iseseisvaks omandamiseks, 16 tundi praktiliste töö ettevalmistamiseks ja ülesannete lahendamiseks.

Independent work is 32 hours. 16 hours of these are devoted to the study of theoretical material, 16 hours - to prepare for the practical exercises and answers to questions.

Computational Vision in Neural and Machine Systems. ISBN 0521862604; 2007 г.
Robert Fisher. Dictionary of Computer Vision and Image Processing ISBN 0470015268; 2005 г.
Milan Sonka, Vaclav Hlavac, Roger Boyle. Image Processing, Analysis, and Machine Vision ISBN 049508252X; 2007 г.
http://www.baltronic.com

-

puudub