A novel marble recognition system using extreme learning machine with LBP and histogram features

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Küçük Resim

Tarih

2021

Dergi Başlığı

Dergi ISSN

Cilt Başlığı

Yayıncı

Wiley

Erişim Hakkı

info:eu-repo/semantics/closedAccess

Özet

Marble classification in production facilities is a sensitive application, which results in light of the subjective decisions of experts. The expert classifies marble manually with its color, homogeneity, and texture in the process. An intelligent marble classifier based on image processing can provide solutions to current problems of the industry. In the proposed study, we introduce an intelligent classifier for marble classification with different classes in real field production. The purpose of the proposed intelligent model for marble facilities is to automate and enhance the manual classification process at present. The real-world dataset consists of Rosso-Levanto, Onyx, Keivan, and Black marble images. Local Binary Patterns and Histogram are used for feature extraction and Extreme Learning Machine is designed as an intelligent classifier. Decision Tree, Support Vector Machine, and Artificial Neural Network structures are also used for thorough performance analysis. The findings (successful test rate of 97.5%) reveal a high performance comparing to existing studies.

Açıklama

Anahtar Kelimeler

extreme learning machine, feature extraction, histogram, LBP, marble classification

Kaynak

Concurrency and Computation-Practice & Experience

WoS Q Değeri

Q3

Scopus Q Değeri

Q1

Cilt

33

Sayı

21

Künye