Multi-class SVM based classification approach for tomato ripeness
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F14%3A86096569" target="_blank" >RIV/61989100:27240/14:86096569 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1007/978-3-319-01781-5_17" target="_blank" >http://dx.doi.org/10.1007/978-3-319-01781-5_17</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-319-01781-5_17" target="_blank" >10.1007/978-3-319-01781-5_17</a>
Alternative languages
Result language
angličtina
Original language name
Multi-class SVM based classification approach for tomato ripeness
Original language description
This article presents a content-based image classification system to monitor the ripeness process of tomato via investigating and classifying the different maturity/ripeness stages. The proposed approach consists of three phases; namely pre-processing, feature extraction, and classification phases. Since tomato surface color is the most important characteristic to observe ripeness, this system uses colored histogram for classifying ripeness stage. It implements Principal Components Analysis (PCA) alongwith Support Vector Machine (SVM) algorithms for feature extraction and classification of ripeness stages, respectively. The datasets used for experiments were constructed based on real sample images for tomato at different stages, which were collected from a farm at Minia city. Datasets of 175 images and 55 images were used as training and testing datasets, respectively. Training dataset is divided into 5 classes representing the different stages of tomato ripeness. Experimental results
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
IN - Informatics
OECD FORD branch
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Result continuities
Project
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Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2014
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Advances in Intelligent Systems and Computing. Volume 237
ISBN
978-3-319-01780-8
ISSN
2194-5357
e-ISSN
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Number of pages
12
Pages from-to
175-186
Publisher name
Springer
Place of publication
Basel
Event location
Ostrava
Event date
Aug 22, 2013
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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