A Novel Texture Classification Method Based on Neutrosophic Truth

Nuh Alpaslan

doi:10.35377/saucis.03.01.709186

EN TR

A Novel Texture Classification Method Based on Neutrosophic Truth

Abstract

Texture analysis is one of the basic procedures used in solving problems in computer vision and image processing. In this study, we propose a new local binary pattern (LBP) method based on neutrosophic set. The proposed method is named as the NZ - LBP. In the proposed NZ - LBP method, the texture image is converted into a neutrosophic set and the texture image is expressed by truth membership set. The local binary pattern features are calculated, by using the neutrosophic truth set instead of the original input image. The neutrosophic membership sets are more resistant to noise than the original input image. The neutrosophic set suppresses noise components, so that edge information can be calculated more accurately. Thus, utilization of the neutrosophic truth set instead of the original image has provided more effective local binary pattern features. The proposed method is able to achieve high classification accuracy with low feature size, reasonable computational cost. Experimental results show that the proposed method increases the accuracy of the local binary pattern method to the classification by approximately 11% without increasing the feature dimension. The obtained results reveal that the proposed method is applicable for real-time applications.

Keywords

Neutrosophic set,local binary pattern,texture classification

Nötrozofik Doğruluk Temelli Yeni Bir Doku Sınıflandırma Yöntemi

Öz

Doku analizi, bilgisayar görmesi ve görüntü işleme alanlarındaki problemlerin çözümünde başvurulan temel işlemlerden biridir. Bu çalışmada, nötrozofik küme temelli yeni bir yerel ikili örüntü (LBP) yöntemi önerilmiştir. Önerilen yöntem NZ - LBP olarak isimlendirilmiştir. Önerilen NZ - LBP yönteminde doku görüntüsü nötrozofik kümeye dönüştürülür ve doku görüntüsü doğruluk üyelik kümesi ile ifade edilir. Görüntünün yerel ikili örüntü öznitelikleri orijinal giriş görüntüsü yerine nötrozofik doğruluk küme görüntüsü kullanılarak hesaplanır. Nötrozofik üyelik kümeleri orijinal giriş görüntüsüne göre gürültüye karşı daha dayanıklıdır. Nötrozofik küme gürültü bileşenlerini baskılar ve bu sayede kenar bilgileri daha doğru bir şekilde hesaplanabilir. Böylece orjinal görüntünün yerine nötrozofik doğruluk kümesinin kullanılması daha etkili yerel ikili örüntü özniteliklerinin elde edilmesini sağlamıştır. Önerilen yöntem düşük öznitelik boyutu, uygun hesaplama maliyeti ile yüksek sınıflandırma doğrulukları elde edebilmiştir. Deneysel sonuçlar önerilen yöntemin öznitelik boyutunu artırmadan yerel ikili örüntü yönteminin sınıflandırma doğruluğunu yaklaşık 11% artırdığını göstermektedir. Elde edilen sonuçlar önerilen yöntemin gerçek zamanlı uygulamalar için uygulanılabilir olduğunu ortaya koymaktadır.

Anahtar Kelimeler

Nötrozofik Küme,yerel ikili örüntü,doku sınıflandırma

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Details

Primary Language

English

Subjects

Artificial Intelligence

Journal Section

Research Article

Authors

Nuh Alpaslan ^*
0000-0002-6828-755X
Türkiye

Publication Date

April 30, 2020

Submission Date

March 25, 2020

Acceptance Date

April 22, 2020

Published in Issue

Year 2020 Volume: 3 Number: 1

DOI

https://doi.org/10.35377/saucis.03.01.709186

IZ

https://izlik.org/JA26CX78RK

Cite

RIS / Bibtex

APA

Alpaslan, N. (2020). A Novel Texture Classification Method Based on Neutrosophic Truth. Sakarya University Journal of Computer and Information Sciences, 3(1), 28-39. https://doi.org/10.35377/saucis.03.01.709186

AMA

1.Alpaslan N. A Novel Texture Classification Method Based on Neutrosophic Truth. SAUCIS. 2020;3(1):28-39. doi:10.35377/saucis.03.01.709186

Chicago

Alpaslan, Nuh. 2020. “A Novel Texture Classification Method Based on Neutrosophic Truth”. Sakarya University Journal of Computer and Information Sciences 3 (1): 28-39. https://doi.org/10.35377/saucis.03.01.709186.

EndNote

Alpaslan N (April 1, 2020) A Novel Texture Classification Method Based on Neutrosophic Truth. Sakarya University Journal of Computer and Information Sciences 3 1 28–39.

IEEE

[1]N. Alpaslan, “A Novel Texture Classification Method Based on Neutrosophic Truth”, SAUCIS, vol. 3, no. 1, pp. 28–39, Apr. 2020, doi: 10.35377/saucis.03.01.709186.

ISNAD

Alpaslan, Nuh. “A Novel Texture Classification Method Based on Neutrosophic Truth”. Sakarya University Journal of Computer and Information Sciences 3/1 (April 1, 2020): 28-39. https://doi.org/10.35377/saucis.03.01.709186.

JAMA

1.Alpaslan N. A Novel Texture Classification Method Based on Neutrosophic Truth. SAUCIS. 2020;3:28–39.

MLA

Alpaslan, Nuh. “A Novel Texture Classification Method Based on Neutrosophic Truth”. Sakarya University Journal of Computer and Information Sciences, vol. 3, no. 1, Apr. 2020, pp. 28-39, doi:10.35377/saucis.03.01.709186.

Vancouver

1.Nuh Alpaslan. A Novel Texture Classification Method Based on Neutrosophic Truth. SAUCIS. 2020 Apr. 1;3(1):28-39. doi:10.35377/saucis.03.01.709186

Cited By

Neutrosophic set based local binary pattern for texture classification

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https://doi.org/10.1016/j.eswa.2022.118350