Texture Classification System Based on 2D-DOST Feature Extraction Method and LS-SVM Classifier

Özal Yıldırım; Ulaş Baran Baloğlu

doi:10.19113/sdufbed.78313

Texture Classification System Based on 2D-DOST Feature Extraction Method and LS-SVM Classifier

Öz

In this paper, a new 2D-DOST (Two-Dimensional Discrete Orthonormal Stockwell Transform) and LS-SVM (Least Squares Support Vector Machines) based classifier system is proposed for classification of texture images. The proposed system contains two main stages. These stages are feature extraction and classification. In the feature extraction stage, the distinguishing feature vectors which represent descriptive features of texture images are obtained by using a 2D-DOST based feature extraction method. In the classification stage, the texture images are classified by the LS-SVM since this classifier has high success rate and accuracy. The training of LS-SVM is performed on the distinguishing feature vector of each texture component. Texture samples are recognized by the test data applied to the input of trained LS-SVM classifier. Performance evaluations of the proposed method are carried on different datasets obtained from sub-images. These datasets include both the normal texture images and noise added images. Sub-images into datasets are derived from Brodatz and Kylberg texture images database. Gaussian and Salt & Pepper noise with different levels are used for creating noisy datasets. According to the study results, the proposed 2D-DOST and LS-SVM based classifier has a capability of classifying texture images with high success rate and noise robustness.

Anahtar Kelimeler

Texture classification,Image processing; Feature extraction

Kaynakça

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Ayrıntılar

Birincil Dil

Türkçe

Konular

-

Bölüm

-

Yazarlar

Özal Yıldırım

Ulaş Baran Baloğlu Bu kişi benim

Yayımlanma Tarihi

7 Haziran 2017

Gönderilme Tarihi

25 Ocak 2017

Kabul Tarihi

-

Yayımlandığı Sayı

Yıl 2017 Cilt: 21 Sayı: 2

DOI

https://doi.org/10.19113/sdufbed.78313

IZ

https://izlik.org/JA79TC65GT

Kaynak Göster

RIS / Bibtex

APA

Yıldırım, Ö., & Baloğlu, U. B. (2017). Texture Classification System Based on 2D-DOST Feature Extraction Method and LS-SVM Classifier. Süleyman Demirel Üniversitesi Fen Bilimleri Enstitüsü Dergisi, 21(2), 350-356. https://doi.org/10.19113/sdufbed.78313

AMA

1.Yıldırım Ö, Baloğlu UB. Texture Classification System Based on 2D-DOST Feature Extraction Method and LS-SVM Classifier. Süleyman Demirel Üniv. Fen Bilim. Enst. Derg. 2017;21(2):350-356. doi:10.19113/sdufbed.78313

Chicago

Yıldırım, Özal, ve Ulaş Baran Baloğlu. 2017. “Texture Classification System Based on 2D-DOST Feature Extraction Method and LS-SVM Classifier”. Süleyman Demirel Üniversitesi Fen Bilimleri Enstitüsü Dergisi 21 (2): 350-56. https://doi.org/10.19113/sdufbed.78313.

EndNote

Yıldırım Ö, Baloğlu UB (01 Ağustos 2017) Texture Classification System Based on 2D-DOST Feature Extraction Method and LS-SVM Classifier. Süleyman Demirel Üniversitesi Fen Bilimleri Enstitüsü Dergisi 21 2 350–356.

IEEE

[1]Ö. Yıldırım ve U. B. Baloğlu, “Texture Classification System Based on 2D-DOST Feature Extraction Method and LS-SVM Classifier”, Süleyman Demirel Üniv. Fen Bilim. Enst. Derg., c. 21, sy 2, ss. 350–356, Ağu. 2017, doi: 10.19113/sdufbed.78313.

ISNAD

Yıldırım, Özal - Baloğlu, Ulaş Baran. “Texture Classification System Based on 2D-DOST Feature Extraction Method and LS-SVM Classifier”. Süleyman Demirel Üniversitesi Fen Bilimleri Enstitüsü Dergisi 21/2 (01 Ağustos 2017): 350-356. https://doi.org/10.19113/sdufbed.78313.

JAMA

1.Yıldırım Ö, Baloğlu UB. Texture Classification System Based on 2D-DOST Feature Extraction Method and LS-SVM Classifier. Süleyman Demirel Üniv. Fen Bilim. Enst. Derg. 2017;21:350–356.

MLA

Yıldırım, Özal, ve Ulaş Baran Baloğlu. “Texture Classification System Based on 2D-DOST Feature Extraction Method and LS-SVM Classifier”. Süleyman Demirel Üniversitesi Fen Bilimleri Enstitüsü Dergisi, c. 21, sy 2, Ağustos 2017, ss. 350-6, doi:10.19113/sdufbed.78313.

Vancouver

1.Özal Yıldırım, Ulaş Baran Baloğlu. Texture Classification System Based on 2D-DOST Feature Extraction Method and LS-SVM Classifier. Süleyman Demirel Üniv. Fen Bilim. Enst. Derg. 01 Ağustos 2017;21(2):350-6. doi:10.19113/sdufbed.78313

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