Leaf classification from binary image via artificial intelligence
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21340%2F16%3A00305211" target="_blank" >RIV/68407700:21340/16:00305211 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1016/j.biosystemseng.2015.12.007" target="_blank" >http://dx.doi.org/10.1016/j.biosystemseng.2015.12.007</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1016/j.biosystemseng.2015.12.007" target="_blank" >10.1016/j.biosystemseng.2015.12.007</a>
Alternative languages
Result language
angličtina
Original language name
Leaf classification from binary image via artificial intelligence
Original language description
The invariant recognition of 2D binary images is the main subject of the paper. Two methods for invariant pattern recognition based on 2D Fourier power spectrum with guaranteed translation invariance are proposed. First method introduce the features invariant to translation, scaling, rotation and mirroring (TSO invariance). The second method introduces the features invariant to general affine transform (A invariance). The methods are used to obtain TSO/A invariant spectra except of the rotation effect which are analysed on circular paths with fixed radii. Harmonic analysis of power fluctuations around paths generates Fourier coefficients and their square absolute values are used as TSO/A invariant descriptors. The proposed methods were tested on two large sets of 2D digital images of tree leaves. After TSO/A invariant processing of thresholded digital images, kernel Support Vector Machine or self-organizing neural network were used for leaf categorisation.
Czech name
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Czech description
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Classification
Type
J<sub>x</sub> - Unclassified - Peer-reviewed scientific article (Jimp, Jsc and Jost)
CEP classification
JD - Use of computers, robotics and its application
OECD FORD branch
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Result continuities
Project
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Continuities
S - Specificky vyzkum na vysokych skolach<br>I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2016
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
BIOSYSTEMS ENGINEERING
ISSN
1537-5110
e-ISSN
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Volume of the periodical
142
Issue of the periodical within the volume
2
Country of publishing house
US - UNITED STATES
Number of pages
18
Pages from-to
83-100
UT code for WoS article
000370100100006
EID of the result in the Scopus database
2-s2.0-84953313019