Digit Classification of Majapahit Relic Inscription  using GLCM-SVM

Tri Septianto; Endang Setyati; Joan Santoso

doi:10.17977/um018v1i22018p46-54

Digit Classification of Majapahit Relic Inscription using GLCM-SVM

Tri Septianto, Endang Setyati, Joan Santoso

Abstract

A higher level of image processing usually contains some kind of classification or recognition. Digit classification is an important subfield in handwritten recognition. Handwritten digits are characterized by large variations so template matching, in general, is inefficient and low in accuracy. In this paper, we propose the classification of the digit of the year of a relic inscription in the Kingdom of Majapahit using Support Vector Machine (SVM). This method is able to cope with very large feature dimensions and without reducing existing features extraction. While the method used for feature extraction using the Gray-Level Co-Occurrence Matrix (GLCM), special for texture analysis. This experiment is divided into 10 classification class, namely: class 1, 2, 3, 4, 5, 6, 7, 8, 9, and class 0. Each class is tested with 10 data so that the whole data testing are 100 data number year. The use of GLCM and SVM methods have obtained an average of classification results about 77 %.

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References

J. Kronenberger, D. Malysiak and U. Handman, "Text and Character Recognition on Metal-sheets," 2017 IEEE International Conference on Information and Automation (ICIA), Macau, 2017, pp. 392-397.

R. Khadijah and A. Nurhadiyatna, "Deep Learning for Handwritten Javanese Character Recognition," 2017 1st International Conference on Informatics and Computational Sciences (ICICoS), Semarang, 2017, pp. 59-64.

Erwin, M. Fachrurrozi, A. Fiqih, B. R. Saputra, R. Algani and A. Primanita, "Content based Image Retrieval for Multi-objects Fruits Recognition using K-means and K-nearest neighbor," 2017 International Conference on Data and Software Engineering (ICoDSE), Palembang, 2017, pp. 1-6.

P. S. Ha and M. Shakeri, "License Plate Automatic Recognition Based on Edge Detection," 2016 Artificial Intelligence and Robotics (IRANOPEN), Qazvin, 2016, pp. 170-174.

H. Hassen and S. Al-Maadeed, "Arabic Handwriting Recognition Using Sequential Minimal Optimization," 2017 1st International Workshop on Arabic Script Analysis and Recognition (ASAR), Nancy, 2017, pp. 79-84.

K. Machhale, H. B. Nandpuru, V. Kapur and L. Kosta, "MRI Brain Cancer Classification Using Hybrid Classifier (SVM-KNN)," 2015 International Conference on Industrial Instrumentation and Control (ICIC), Pune, 2015, pp. 60-65.

M. Mohamed Fathima, D. Manimegalai and S. Thaiyalnayaki, "Automatic Detection of Tumor Subtype in Mammograms Based on GLCM and DWT Feature Using SVM," 2013 International Conference on Information Communication and Embedded Systems (ICICES), Chennai, 2013, pp. 809-813.

A. Patle and T. V. Kalyani, "Support Vector Machine with Inverse Fringe as Feature for MNIST Dataset," 2016 IEEE 6th International Conference on Advanced Computing (IACC), Bhimavaram, 2016, pp. 123-126.

V. Wasule and P. Sonar, "Classification of Brain MRI Using SVM and KNN Classifier," 2017 Third International Conference on Sensing, Signal Processing and Security (ICSSS), Chennai, 2017, pp. 218-223.

R. Asery, R. K. Sunkaria, L. D. Sharma and A. Kumar, "Fog detection using GLCM based features and SVM," 2016 Conference on Advances in Signal Processing (CASP), Pune, 2016, pp. 72-76.

M. Imani and G. A. Montazer, "GLCM Features and Fuzzy Nearest Neighbor Classifier for Emotion Recognition from Face," 2017 7th International Conference on Computer and Knowledge Engineering (ICCKE), Mashhad, 2017, pp. 8-13.

Y. L. Lei, X. M. Zhao and W. D. Guo, "Cirrhosis Recognition of Liver Ultrasound Images Based on SVM and Uniform LBP Feature," 2015 IEEE Advanced Information Technology, Electronic and Automation Control Conference (IAEAC), Chongqing, 2015, pp. 382-387.

S. Daliman, S. A. Rahman, S. A. Bakar and I. Busu, "Segmentation of Oil Palm Area Based on GLCM-SVM and NDVI," 2014 IEEE Region 10 Symposium, Kuala Lumpur, 2014, pp. 645-650.

G. Kesavaraj and S. Sukumaran, "A study on classification techniques in data mining," 2013 IEEE Fourth International Conference on Computing, Communications and Networking Technologies (ICCCNT), Tiruchengode, India, 2013, pp. 1-7.

Arti Patle and Deepak Singh Chouhan, “SVM Kernel Functions for Classification”, 2013 International Conference on Advances in Technology and Engineering (ICATE), Mumbai, 23-25 January 2013, Paper Identification Number-102.

DOI: http://dx.doi.org/10.17977/um018v1i22018p46-54