PENGAMBILAN FITUR ANGKA JAWA MENGGUNAKAN SHADOW FEATURE EXTRACTION
Abstract
Many Applications developed to recognition handwritten called Optical Character Recognition (OCR), who generally it only presented alphabet recognition. Javanese numbers (aksara wilangan) or Javanese characters are culture of Indonesia from great grandmother and must be knowed by rising genereation. The final project presented “Get Character Feature Handwriting Javanese Numbers Used Shadow Feature Extraction Method and Multi Layer Perceptron (MLP). The shadow feature method used to recognition characterstic of handwritten before it classification by MLP. Application test have two stage that is a sample training test 100 of data set and sample testing test 50 of data set. Percentage successed pattern concerning training samples 99% and error recognition 0,10%, whereas testing samples 90,8% and error recognition 9,2%.
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Basu, S., dkk., 2005, Handwritten ‘Bangla’ Alphabet Recognition using an MLP Based Classifier, Proceeding of the 2nd National Conference on Computer Processing of Bangla, hal. 285 – 291. Dhaka.
Basu, S., dkk., 2005, An MLP Based Approach for Recognition of Handwritten ‘Bangla’ Numerals, Proceeding 2nd Indian International Conference on Artificial Intelligence, hal. 407 – 417. Pune.
Chaudhuri, B.B. dan Bhattacharya, U., 2000, Efficient Training and Improved Performance of Multilayer Perceptron in Pattern Classification, Neurocomputing, vol. 34, hal. 11-27.
Darusuprapta, dkk., 2002, Pedoman Penulisan Aksara Jawa, Yayasan Pustaka Nusatama, Yogyakarta.
Das, N., dkk., 2006, Handwritten Arabic Numeral Recognition using a Multi layerPerceptron, Proceeding National Conference on Recent Trends in Information Systems, hal. 200 – 203.
Das, N., dkk., 2010, Handwritten Bangla Basic and Compound Character Recognition Using MLP and SVM, Journal of Computing, Vol. 2, No. 2, hal. 109 – 115.
Fausett, L. 2006. Fundamentals of Neural Networks. Prentice-Hall, New York.
Fiset, R., dkk., 1998, Map-Image Matching Using a Multi-Layerperceptron: The Case of the Road Network, ISPRS Journal of Photogrammetry and Remote Sensing, vol. 53, hal. 76-84.
Ham, F.M. dan Kostanic, I., 2001, Principles of Neurocomputing for Science & Engineering. McGraw-Hill, New York.
Hasibuan, F.M., 2011, Desain dan Implementasi Sistem Penerjemah Aksara Jawa Ke Huruf Latin Berbasis Pengolahan Citra Digital dan Jaringan Syaraf Tiruan Self-Organizing Map (SOM), Tugas Akhir Mahasiswa Institut Teknologi Telkom.
Kiong, L.V., 2006, Visual Basic 6 Made Easy, ISBN: 141962895X, 2006
Mukherjee, S., 2010, Recognition of Handwritten Bengali Character Based On Character Features, (M.Tech IT Thesis), Jadavpur University, Kolkata, India.
McCulloch, W.S. dan Pitts, W., 1943, A Logical Calculus of the Ideas Immanent in Nervous Activity, Bulletin of Mathematical Biophysis, vol 5: hal. 115-133.
Nurtanio, Inggrid, Astuti, E. R., Purnama, I. K. E.,Hariadi, M., Purnomo, M. H., Classifying Cyst and Tumor Lesion Using Support Vector Machine Based on Dental Panoramic Images Texture Features, IAENG International Journal of Computer Science, vol. 40, no. 1, Feb. 2013.
Rosenblatt, F., 1958, The Perceptron: A Probabilistic Model for Information Storage and Organization in the Brain, Psychological Review, vol. 5: hal 368-408.
Rumelhart, D.E. dkk., 1986, Learning Representations by Back-Propagating Errors. Nature, vol. 323: hal. 533-536.
Wibowo, M.C. dan Wirakusuma, S., 2013, Pengenalan Pola Tulisan Tangan Aksara Jawa “Ha Na Ca Ra Ka” Menggunakan Multi Layer Perceptron, Prosiding Seminar Nasional Teknologi Informasi (SNASTI) 2013, Oktober 2013, Surabaya, hal. ICCS-27 – ICCS-32
Zhang, Z. dkk., 1998, Comparison Between Geometry-Based and Gabor-Wavelets-Based Facial Expression Recognition Using Multi-Layer Perceptron. Automatic Face and Gesture Recognition. Third IEEE International Conference. Naara
Trier O.D., Anil K.J., dan Torfinn,T. ,” Feature Extraction methods for Character Recognition –A survey “, Pattern Recognition, Vol29, No.4, pp-641-662, 1996
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