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| Image Recognition With the Help of Auto-Associative Neural Network
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Full
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Source |
International Journal of Computer Science and Security (IJCSS) |
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Table of Contents |
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Complete Issue PDF(3.68MB) |
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Volume: 5 Issue: 1 |
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Pages: 1-167 |
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Publication
Date: March / April 2011 |
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ISSN
(Online): 1985-1553 |
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Pages |
54 - 63 |
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Author(s) |
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Published
Date |
04-04-2011 |
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Publisher |
CSC
Journals, Kuala Lumpur,
Malaysia |
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ADDITIONAL
INFORMATION |
| Keywords Abstract References Cited by Related Articles Collaborative
Colleague |
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KEYWORDS: Image Recognition, Associative Memory, Pattern Matching, Artificial Neural Network, Weight Matrix |
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| This paper proposes a Neural Network model that has been utilized for image recognition. The main issue of Neural Network model here is to train the system for image recognition. In this paper the NN model has been prepared in MATLAB platform. The NN model uses Auto-Associative memory for training. The model reads the image in the form of a matrix, evaluates the weight matrix associated with the image. After training process is done, whenever the image is provided to the system the model recognizes it appropriately. The weight matrix evaluated here is used for image pattern matching. It is noticed that the model developed is accurate enough to recognize the image even if the image is distorted or some portion/ data is missing from the image. This model eliminates the long time consuming process of image recognition |
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FOR CONFERENCES : Csurka, G., Dance, c., Bray, c., and Fan, L., "Visual categorization with bags of key points," In Proceedings Workshop on Statistical Learning in Computer Vision, I -22, 2004.
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FOR BOOKS: Simon Haykin, “Neural Networks A Comprehensive Foundation”, Pearson Educartion (Singapore) Pvt. Ltd. pp. 1-49 (2004).
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FOR BOOKS : S.N. Sivanandam, S. Sumathi, S.N. Deepa, “Introduction to Neural Networks using Matlab 6.0”, Tata McGraw-Hill pp. 10-29, pp 109-165(2006).
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| Moumi Pandit : Colleagues
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| Mousumi Gupta : Colleagues
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