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Title:AVTOMATSKO PREPOZNAVANJE NOSU IZ DIGITALNIH POSNETKOV S POSTOPKI RAČUNALNIŠKEGA VIDA
Authors:ID Kotnik, Jadran (Author)
ID Potočnik, Božidar (Mentor) More about this mentor... New window
Files:.pdf UN_Kotnik_Jadran_2015.pdf (1,99 MB)
MD5: E6AC05B04FBA3E45C995547270257FA5
 
Language:Slovenian
Work type:Bachelor thesis/paper
Typology:2.11 - Undergraduate Thesis
Organization:FERI - Faculty of Electrical Engineering and Computer Science
Abstract:V tem diplomskem delu se ukvarjamo z avtomatskim razpoznavanjem nosu in njegovo segmentacijo v digitalnih posnetkih. Rezultat našega dela je algoritem, ki vrača natančen obris nosu. Za razpoznavanje obrobe nosu smo uporabili modele, za iskanje konice nosu in nosnic pa smo uporabili iskanje svetlejših oziroma temnejših področij. Uspešnost našega algoritma smo nato preverili na zbirki 50 slik. Ugotovili smo, da je razpoznavanje obrobe nosu v večini slik dobro, razen v izjemnih primerih, kjer razpoznamo napačni del slike. Če uporabimo za prepoznavanje nosu modele, potem je bila Hausdorffova razdalja v povprečju enaka 3,221 mm s standardnim odklonom 2,320 mm, t.i. povprečna Hausdorffova razdalja pa je bila v povprečju 1,080 mm s standardnim odklonom 0,696 mm. Algoritem na izhodu oblikuje maske prepoznanih komponent nosu, katere lahko uporabimo v naprednejših aplikacijah.
Keywords:računalniški vid, prepoznavanje nosu, razpoznavanje vzorcev, digitalna obdelava slik
Place of publishing:[Maribor
Publisher:J. Kotnik
Year of publishing:2015
PID:20.500.12556/DKUM-54495 New window
UDC:004.932(043.2)
COBISS.SI-ID:19311382 New window
NUK URN:URN:SI:UM:DK:KQI43IWP
Publication date in DKUM:15.10.2015
Views:2351
Downloads:110
Metadata:XML DC-XML DC-RDF
Categories:KTFMB - FERI
:
KOTNIK, Jadran, 2015, AVTOMATSKO PREPOZNAVANJE NOSU IZ DIGITALNIH POSNETKOV S POSTOPKI RAČUNALNIŠKEGA VIDA [online]. Bachelor’s thesis. Maribor : J. Kotnik. [Accessed 5 April 2025]. Retrieved from: https://dk.um.si/IzpisGradiva.php?lang=eng&id=54495
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Secondary language

Language:English
Title:AUTOMATED NOSE RECOGNITION FROM DIGITAL IMAGES BY COMPUTER VISION PROCEDURES
Abstract:In this thesis, we are dealing with automatic nose recognition and segmentation in digital images. The result of our work is an algorithm that returns an accurate nose trim. We used models for nose trim recognition and searching of brighter or darker areas for the nose tip and nostril recognition. We verified the success rate of our algorithm on a set of 50 images. We have found that for most images the nose trim is recognized in a good measure, with the exception of extreme cases, where we recognize the wrong part of the image. When we use models for nose recognition the Hausdorff distance averages at 3.221 mm with a standard deviation of 2.320 mm while the so called average Hausdorff distance averages at 1.080 mm with a standard deviation of 0.696 mm. The algorithm forms mask images as the output. The output of our algorithm are mask images that can be used in more advanced applications.
Keywords:computer vision, nose recognition pattern recognition, digital image processing


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