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Title:PREPOZNAVA PROMETNIH ZNAKOV Z UPORABO POSTOPKOV RAČUNALNIŠKEGA VIDA
Authors:ID Lenič, Matjaž (Author)
ID Potočnik, Božidar (Mentor) More about this mentor... New window
Files:.pdf UNI_Lenic_Matjaz_2010.pdf (2,14 MB)
MD5: 75C17B3EC8FBB1B905CF6381D69EFCB0
PID: 20.500.12556/dkum/05ddcd9a-ef84-4948-afbf-5769a00306a5
 
Language:Slovenian
Work type:Bachelor thesis/paper
Organization:FERI - Faculty of Electrical Engineering and Computer Science
Abstract:V sodobnih avtomobilih najdemo vse več pomoči vozniku: sisteme proti zdrsavanju koles, pomoč pri zaviranju, sisteme za avtomatsko parkiranje itd. Ena izmed takih pomoči je razpoznava prometnih znakov. Razpoznava prometnih znakov, ki jo ponujajo proizvajalci avtomobilov, razpoznava le omejitve hitrosti, ne pa drugih pomembnih znakov, kot so znaki za nevarnost ali znaki za izrecne odredbe. Ker so to prometni znaki, ki so pomembni, smo v tem diplomskem delu razvili preprost, a vseeno učinkovit sistem za njihovo prepoznavanje. Ta sistem temelji na segmentaciji s pragovno operacijo v različnih barvnih prostorih in iskanju osnovnih geometrijskih oblik z uporabo preprostih šablon. Rezultati kažejo, da tak pristop učinkovito prepoznava okrogle in trikotne znake, prepoznava štirikotnih znakov pa je nezanesljiva. Za uspešnejšo prepoznavanje le-teh pa je potrebnih še nekaj dodelav, ki jih v delu tudi predlagamo.
Keywords:prometni znaki, prepoznava, obdelava digitalnih slik, segmentacija, računalniški vid
Place of publishing:Maribor
Publisher:[M. Lenič]
Year of publishing:2010
PID:20.500.12556/DKUM-17109 New window
UDC:004.89:656.1(043.2)
COBISS.SI-ID:14822166 New window
NUK URN:URN:SI:UM:DK:PLGCWKQO
Publication date in DKUM:14.01.2011
Views:3694
Downloads:265
Metadata:XML DC-XML DC-RDF
Categories:KTFMB - FERI
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Secondary language

Language:English
Title:RECOGNITION OF TRAFFIC SIGNS BY USING COMPUTER VISION PROCEDURES
Abstract:There are more and more driving assistances in modern cars: traction control system, braking assistance, system for automatic parking etc. Among them you will also find traffic sign recognition. The traffic sign recognition, which is offered by car manufacturers recognizes only speed limit signs, but not other important signs, such as danger warning or prohibitory signs. In this diploma work, we implemented a simple, yet efficient system that identifies these signs aswell. The system is based on thresholding in different colour spaces and on searching for basic geometric shapes by using very simple templates. Results point out that such an approach effectivelly identifies circular and triangular traffic signs, but is unreliable at identifing rectangular traffic signs. This system still needs some modifications (which are also suggested in this work) to effectivelly identify such traffic signs.
Keywords:traffic signs, identification/recognition, digital image processing, segmentation, computer vision


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