Detection and classification of hazelnut fruit by using image processing techniques and clustering methods

In this study, theobjects found in the environment are detected and classified in real time, theresults obtained are presented. Hazelnut fruit is used in the experimentalstudies of the proposed method. The image belongs to hazelnut that is in a workenvironment is taken with the camera, it is process...

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Main Authors: Serdar Solak, Umut Altınışık
Format: Article
Language:English
Published: Sakarya University 2018-02-01
Series:Sakarya Üniversitesi Fen Bilimleri Enstitüsü Dergisi
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Online Access:https://dergipark.org.tr/tr/download/article-file/340880
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author Serdar Solak
Umut Altınışık
author_facet Serdar Solak
Umut Altınışık
author_sort Serdar Solak
collection DOAJ
description In this study, theobjects found in the environment are detected and classified in real time, theresults obtained are presented. Hazelnut fruit is used in the experimentalstudies of the proposed method. The image belongs to hazelnut that is in a workenvironment is taken with the camera, it is processed by using image processingtechniques. The size and area data of hazelnut on the image plane iscalculated. By evaluating the obtained data, the hazelnut is divided into threeclasses as small (K1), medium (K2) and big (K3) in real time application. Thisprocess is performed using mean-based classification and K-means clusteringmethods. Detection and classification of cluster centers is provided by usingthe information database obtained from the data of hazelnut fruit. Hazelnutfruits found in the experimental environment are determined with 100% accuracyusing image processing techniques. The classification of hazelnut fruits usingthe mean-based and K-means clustering methods has been compared. As a result ofthe comparison, it is observed that the two methods realized are similar ratioof 90% to 100%.
format Article
id doaj-art-01c534839c2c43a7bd8a7dcbf439f3c4
institution Kabale University
issn 2147-835X
language English
publishDate 2018-02-01
publisher Sakarya University
record_format Article
series Sakarya Üniversitesi Fen Bilimleri Enstitüsü Dergisi
spelling doaj-art-01c534839c2c43a7bd8a7dcbf439f3c42024-12-23T07:57:11ZengSakarya UniversitySakarya Üniversitesi Fen Bilimleri Enstitüsü Dergisi2147-835X2018-02-01221566510.16984/saufenbilder.30385028Detection and classification of hazelnut fruit by using image processing techniques and clustering methodsSerdar Solak0Umut Altınışık1KOCAELİ ÜNİVERSİTESİKOCAELİ ÜNİVERSİTESİIn this study, theobjects found in the environment are detected and classified in real time, theresults obtained are presented. Hazelnut fruit is used in the experimentalstudies of the proposed method. The image belongs to hazelnut that is in a workenvironment is taken with the camera, it is processed by using image processingtechniques. The size and area data of hazelnut on the image plane iscalculated. By evaluating the obtained data, the hazelnut is divided into threeclasses as small (K1), medium (K2) and big (K3) in real time application. Thisprocess is performed using mean-based classification and K-means clusteringmethods. Detection and classification of cluster centers is provided by usingthe information database obtained from the data of hazelnut fruit. Hazelnutfruits found in the experimental environment are determined with 100% accuracyusing image processing techniques. The classification of hazelnut fruits usingthe mean-based and K-means clustering methods has been compared. As a result ofthe comparison, it is observed that the two methods realized are similar ratioof 90% to 100%.https://dergipark.org.tr/tr/download/article-file/340880image processingobject detectionmorphologymomentumclusteringgörüntü i̇şlemenesne tespitimorfolojimomentkümeleme
spellingShingle Serdar Solak
Umut Altınışık
Detection and classification of hazelnut fruit by using image processing techniques and clustering methods
Sakarya Üniversitesi Fen Bilimleri Enstitüsü Dergisi
image processing
object detection
morphology
momentum
clustering
görüntü i̇şleme
nesne tespiti
morfoloji
moment
kümeleme
title Detection and classification of hazelnut fruit by using image processing techniques and clustering methods
title_full Detection and classification of hazelnut fruit by using image processing techniques and clustering methods
title_fullStr Detection and classification of hazelnut fruit by using image processing techniques and clustering methods
title_full_unstemmed Detection and classification of hazelnut fruit by using image processing techniques and clustering methods
title_short Detection and classification of hazelnut fruit by using image processing techniques and clustering methods
title_sort detection and classification of hazelnut fruit by using image processing techniques and clustering methods
topic image processing
object detection
morphology
momentum
clustering
görüntü i̇şleme
nesne tespiti
morfoloji
moment
kümeleme
url https://dergipark.org.tr/tr/download/article-file/340880
work_keys_str_mv AT serdarsolak detectionandclassificationofhazelnutfruitbyusingimageprocessingtechniquesandclusteringmethods
AT umutaltınısık detectionandclassificationofhazelnutfruitbyusingimageprocessingtechniquesandclusteringmethods