International Journal of Information Technology and Computer Science (IJITCS)
IJITCS Vol. 4, No. 5, 8 May 2012
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Image Classification using Support Vector Machine and Artificial Neural Network
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Author(s)
Index Terms
Image classification, support vector machine, artificial neural network
Abstract
Image classification is one of classical problems of concern in image processing. There are various approaches for solving this problem. The aim of this paper is bring together two areas in which are Artificial Neural Network (ANN) and Support Vector Machine (SVM) applying for image classification. Firstly, we separate the image into many sub-images based on the features of images. Each sub-image is classified into the responsive class by an ANN. Finally, SVM has been compiled all the classify result of ANN. Our proposal classification model has brought together many ANN and one SVM. Let it denote ANN_SVM. ANN_SVM has been applied for Roman numerals recognition application and the precision rate is 86%. The experimental results show the feasibility of our proposal model.
Cite This Paper
Le Hoang Thai, Tran Son Hai, Nguyen Thanh Thuy, "Image Classification using Support Vector Machine and Artificial Neural Network", International Journal of Information Technology and Computer Science(IJITCS), vol.4, no.5, pp.32-38, 2012. DOI:10.5815/ijitcs.2012.05.05
Reference
[1]D. Lu, Q. WENG, A survey of image classification methods and techniques for improving classification performance, International Journal of Remote Sensing, 2007, Vol. 28, No. 5, pp.823-870.
[2]Qing Chen, Real-time Vision-based Hand Gesture Recognition Using Haar-like Features, Instrumentation and Measurement Technology Conference Proceedings, 2007. IMTC 2007. IEEE, 2007, pp.1-6
[3]Thai Hoang Le, Applications of Artificial Neural Networks to Facial Image Processing, Artificial Neural Networks - Application, Dr. Chi Leung Patrick Hui (Ed.), ISBN: 978-953-307-188-6, InTech, Available from: http://www.intechopen.com/books/artificial-neural-networks-application/applications-of-artificial-neural-networks-to-facial-image-processing, 2011, pp. 213-240
[4]Thai Le, Phat Tat, Hai Tran, Facial Expression Classification based on Multi Artificial Neural Network and Two Dimensional Principal Component Analysis, International Journal of Computer Science Issue (IJCSI), 2011, Vol. 8, No. 3, pp. 19-26.
[5]Mohammadmehdi Bozorgi, Mohd Aizaini Maarof, and Lee Zhi Sam, Multi-classifier Scheme with Low-Level Visual Feature for Adult Image Classification, Springer, Communications in Computer and Information Science, 2011, Vol. 181, No. 6, pp. 793-802
[6]D. Zhang, Z.-H. Zhou, and S. Chen, Diagonal principal component analysis for face recognition, Pattern Recognition, 2006, Vol. 39, pp. 140-142.
[7]Thai Hoang Le, Nguyen Thai Do Nguyen, Hai Son Tran, Facial Expression Classification System Integrating Canny, Principal Component Analysis and Artificial Neural Network, 3rd International Conference on Machine Learning and Computing, ICMLC Proceedings, 2011, Vol. 4, pp. 306-309.
[8]V.H. Nguyen, Facial Feature Extraction Based on Wavelet Transform, Artificial Intelligence and Computational Intelligence, Lecture Notes in Computer Science, 2009, Vol. 5855/2009, pp. 330-339, DOI: 10.1007/978-3-642-05253-8_37
[9]Bishop, C.: Pattern Recognition and Machine Learning. Springer Press, 2006
[10]Hao Jiang, Wai-Ki Ching,Zeyu Zheng,"Kernel Techniques in Support Vector Machines for Classification of Biological Data", IJITCS, 2011, Vol.3, No.2, pp.1-8.
[11]Haiyan Li,Guo Lei,Zhang Yufeng,Xinling Shi,Chen Jianhua, A Novel Method for Grayscale Image Segmentation by Using GIT-PCANN, IJITCS, 2011, Vol.3, No.5, pp.12-18, DOI:10.5815/ijitcs.2011.05.02
[12]Nilima Kulkarni, Color Thresholding Method for Image Segmentation of Natural Images, IJIGSP, 2012, Vol.4, No.1, pp.28-34, DOI: 10.5815/ijigsp.2012.01.04
[13]Le Hoang Thai, Tran Son Hai, Facial Expression Classification Based on Multi Artificial Neural Network, International conference on Advance Computing and Applications, 2010, Volume of Extended Abstract, pp. 125-133
[14]Thai Hoang Le., Nguyen Do Thai Nguyen, Hai Son Tran, Landscape Image of Regional Tourism Classification using Neural Network, the 3rd International Conference on Communications and Electronics, ICCE 2010. Proceedings
[15]G.M. Foody, A. Mathur, A relative evaluation of multiclass image classification by support vector machines, Geoscience and Remote Sensing, IEEE Transactions, 2004, Vol. 42, No. 6, pp.1335-1343
[16]Yang Mingqiang, Kpalma Kidiyo, Ronsin Joseph, A survey of shape feature extraction techniques, Pattern Recognition, Peng-Yeng Yin (Ed.), 2008, pp.43-90