Could k-nn classifier be useful in tree leaves recognition

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21340%2F14%3A00223989" target="_blank" >RIV/68407700:21340/14:00223989 - isvavai.cz</a>

Výsledek na webu

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DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Could k-nn classifier be useful in tree leaves recognition

Popis výsledku v původním jazyce

This paper presents a method for affine invariant recognition of two-dimensional binary objects based on 2D Fourier power spectrum. Such function is translation invariant and their moments of second order enable construction of affine invariant spectrumexcept of the rotation effect. Harmonic analysis of samples on circular paths generates Fourier coefficients whose absolute values are affine invariant descriptors. Affine invariancy is approximately saved also for large digital binary images as demonstrated in the experimental part. The proposed method is tested on artificial data set first and consequently on a large set of 2D binary digital images of tree leaves. High dimensionality of feature vectors is reduced via the kernel PCA technique with Gaussian kernel and the k-NN classifier is used for image classification. The results are summarized as k-NN classifier sensitivity after dimensionality reduction. The resulting descriptors after dimensionality reduction are able to distingui

Název v anglickém jazyce

Could k-nn classifier be useful in tree leaves recognition

Popis výsledku anglicky

This paper presents a method for affine invariant recognition of two-dimensional binary objects based on 2D Fourier power spectrum. Such function is translation invariant and their moments of second order enable construction of affine invariant spectrumexcept of the rotation effect. Harmonic analysis of samples on circular paths generates Fourier coefficients whose absolute values are affine invariant descriptors. Affine invariancy is approximately saved also for large digital binary images as demonstrated in the experimental part. The proposed method is tested on artificial data set first and consequently on a large set of 2D binary digital images of tree leaves. High dimensionality of feature vectors is reduced via the kernel PCA technique with Gaussian kernel and the k-NN classifier is used for image classification. The results are summarized as k-NN classifier sensitivity after dimensionality reduction. The resulting descriptors after dimensionality reduction are able to distingui

Druh

J_x - Nezařazeno - Článek v odborném periodiku (Jimp, Jsc a Jost)

CEP obor

JD - Využití počítačů, robotika a její aplikace

OECD FORD obor

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Projekt

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Návaznosti

S - Specificky vyzkum na vysokych skolach<br>I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2014

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

ARCHIVES OF CONTROL SCIENCES

ISSN

1230-2384

e-ISSN

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Svazek periodika

24

Číslo periodika v rámci svazku

2

Stát vydavatele periodika

PL - Polská republika

Počet stran výsledku

16

Strana od-do

177-192

Kód UT WoS článku

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EID výsledku v databázi Scopus

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