Author:
Hamzidah Nurul Khaerani,Jariyah Ainun,Ramadhani Annisa Resky,Nurhasni Nurhasni,Parenreng Mardawia Mabe,Suyuti Saidah
Reference12 articles.
1. A Novel Machine-Learning Framework-based on LBP and GLCM Approaches for CBIR System
2. F. Robi, R. Magdalena, and I. Wijayanto, “Rancang Bangun Aplikasi Deteksi Motif Batik Berbasis Pengolahan Citra Digital pada Platform Android Designing Application Of Motif Batik Detection Base on Digital Image Prcessing In Android Platform,” E-Proceeding of Engineering 1(1), 310–318 (2014).
3. T. Sutojo, P.S. Tirajani, D.R. Ignatius Moses Setiadi, C.A. Sari, and E.H. Rachmawanto, "CBIR for classification of cow types using GLCM and color features extraction," in 2017 2nd International Conferences on Information Technology, Information Systems and Electrical Engineering (ICITISEE) (IEEE, Yogyakarta, Indonesia, 2017), pp. 182–187.
4. R.M. Rasli, T.Z.T. Muda, Y. Yusof, and J.A. Bakar, "Comparative Analysis of Content Based Image Retrieval Techniques Using Color Histogram: A Case Study of GLCM and K-Means Clustering," in 2012 Third International Conference on Intelligent Systems Modelling and Simulation (IEEE, Kota Kinabalu, Malaysia, 2012), pp. 283–286.
5. Y. Rullist, B. Irawan, and A.B. Osmond, “Aplikasi Identifikasi Motif Batik Menggunakan Metode Ekstraksi Fitur Gray Level Co-occurrence Matrix (GLCM) Berbasis Android,” E-Proceeding of Engineering 2(2), 3684–3692 (2015).