PREPOZNAVANJE PRIMERKA IZ GENERIČNEGA RAZREDA OBJEKTOV NA OSNOVI DIGITALNIH SLIK

Dimovska, Natalija

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Title:	PREPOZNAVANJE PRIMERKA IZ GENERIČNEGA RAZREDA OBJEKTOV NA OSNOVI DIGITALNIH SLIK
Authors:	ID Dimovska, Natalija (Author) ID Potočnik, Božidar (Mentor) More about this mentor...
Files:	UN_Dimovska_Natalija_2015.pdf (2,04 MB) MD5: 5A009ECB91414D0925928ED376C273F8
Language:	Slovenian
Work type:	Bachelor thesis/paper
Typology:	2.11 - Undergraduate Thesis
Organization:	FERI - Faculty of Electrical Engineering and Computer Science
Abstract:	V diplomskem delu je predstavljena metoda za prepoznavanje primerka iz generičnega razreda objektov na osnovi digitalnih slik. Proces prepoznavanja objekta na sliki je ena od hitro razvijajočih se tehnologij. Podajamo pregled že obstoječih metod in postopkov za segmentacijo, strojno učenje ter popis objektov z značilkami. Prav tako je opisana naša implementacija algoritma za prepoznavanje generičnih objektov na sliki. Prepoznavanje primerka (skodelic) smo izvedli s segmentacijo GrubCut, deskriptorji HOG (angl. Histogram of Oriented Gradients), za klasifikacijo primerka pa smo uporabili strojno učenje s stroji SVM (angl. Support Vector Machine). Na testni množici 34 slik z 75 primerki smo izračunali metriko TPR (angl. True Positive Rate) kot 0,92 in metriko PPV (angl. Positive Predicted Value) skoraj 0,96, pri čemer smo uporabili učno množico velikosti 84 slik.
Keywords:	Prepoznavanje objektov, klasifikacija, zaznavanje objektov, deskriptor, HOG, SVM, segmentacija
Place of publishing:	[Maribor
Publisher:	N. Dimovska
Year of publishing:	2015
PID:	20.500.12556/DKUM-54261
UDC:	004.932(043.2)
COBISS.SI-ID:	19094294
NUK URN:	URN:SI:UM:DK:BACPPRKN
Publication date in DKUM:	14.10.2015
Views:	1437
Downloads:	109
Metadata:
Categories:	KTFMB - FERI
:	DIMOVSKA, Natalija, 2015, PREPOZNAVANJE PRIMERKA IZ GENERIČNEGA RAZREDA OBJEKTOV NA OSNOVI DIGITALNIH SLIK [online]. Bachelor’s thesis. Maribor : N. Dimovska. [Accessed 23 April 2025]. Retrieved from: https://dk.um.si/IzpisGradiva.php?lang=eng&id=54261 Copy citation

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Secondary language

Language:	English
Title:	IDENTIFYING AN INSTANCE OF A GENERIC CLASS OF OBJECTS BASED ON DIGITAL IMAGES
Abstract:	In this diploma work is presented a method for identifying an instance of a generic class of objects based on digital images. The process of identifying object in an image is one of the technologies that is rapidly developing nowadays. In this diploma work we present an overview of the existing methods and procedures for segmentation, machine learning and descriptors. In the main part is descibed our implementation of the algorithm for identifying generic object in an image. Identifying objects (cups) we preformed by using GrubCut segmentation, HOG (Histogram of Oriented Gradients) descriptors and for object classification we have used SVM (Support Vector Machine). On the testing dataset with 34 images with 75 instances, we have calculated the TPR (True Positive Rate) metric as 0,92 and PPV (Positive Predictive Value) metric as almost 0,96, where we have used learning dataset with 84 images.
Keywords:	Identifying objects, classification, object detection, descriptors, HOG, SVM, segmentation

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