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Title:Nadzorni sistem in zaznava objektov na sliki, zajeti z brezžično kamero : diplomsko delo
Authors:ID Zgaga, Bine (Author)
ID Holobar, Aleš (Mentor) More about this mentor... New window
Files:.pdf UN_Zgaga_Bine_2023.pdf (1,86 MB)
MD5: 63157B4CB3A87BD276523A47CE21319E
 
Language:Slovenian
Work type:Bachelor thesis/paper
Typology:2.11 - Undergraduate Thesis
Organization:FERI - Faculty of Electrical Engineering and Computer Science
Abstract:Diplomsko delo obsega študijo algoritmov razpoznavanja objektov iz slik, zajetih z brezžično kamero ter razvoj sistema, ki omogoča nadzorovanje in varovanje posesti uporabnika. V uvodnem delu analiziramo obstoječe rešitve z vidika njihovih implementacij, prednosti in slabosti ter izberemo najbolj primerne metode kot osnovo za naše delo. V nadaljevanju predstavimo kamero Raspberry Pi, ki jo bomo uporabili za zajemanje slik, uporabljene algoritme in njihovo delovanje ter implementacijo. Učinkovitost rešitve dokažemo z rezultati razpoznavanja objektov, diplomsko nalogo pa zaključimo s primerjavo učinkovitosti naše rešitve z že obstoječimi.
Keywords:razpoznavanje objektov, internet stvari, nadzorni sistemi.
Place of publishing:Maribor
Place of performance:Maribor
Publisher:[B. Zgaga]
Year of publishing:2023
Number of pages:1 spletni vir (1 datoteka PDF ([XI], 45 f.))
PID:20.500.12556/DKUM-85012 New window
UDC:004.932.72'1(043.2)
COBISS.SI-ID:184617219 New window
Publication date in DKUM:21.09.2023
Views:493
Downloads:60
Metadata:XML DC-XML DC-RDF
Categories:KTFMB - FERI
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Licences

License:CC BY-NC-ND 4.0, Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International
Link:http://creativecommons.org/licenses/by-nc-nd/4.0/
Description:The most restrictive Creative Commons license. This only allows people to download and share the work for no commercial gain and for no other purposes.
Licensing start date:16.08.2023

Secondary language

Language:English
Title:Surveillance system and object detection in wireless camera captured images
Abstract:In our thesis we conduct a study of object recognition algorithms and develop a surveillance system that allows the control and protection of the user's property. In the introductory part, we analyse the existing solutions in terms of their implementations, advantages and disadvantages, and select the most appropriate methods as a basis for our work. Afterwards, we present the Raspberry Pi camera, which is used for capturing images, the algorithms used and their operation and implementation. The effectiveness of the solution is proven by the results of object recognition. The diploma thesis is concluded by comparing the efficiency of our solution with existing solutions.
Keywords:object recognition, internet of things, surveillance systems.


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