Image classification based on textural features using Artificial Neural Network (ANN)

Shah, Satish and Gandhi, Vaibhav (2004) Image classification based on textural features using Artificial Neural Network (ANN). Journal of The Institution of Engineers (India): Series A, 84 . pp. 72-77. ISSN 2250-2149

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Abstract

Image classification plays an important part in the fields of Remote sensing, Image analysis and Pattern recognition.
Digital image classification is the process of sorting all the pixels in an image into a finite number of individual classes.
The conventional statistical approaches for land cover classification use only the gray values. However, they lead to
misclassification due to strictly convex boundaries. Textural features can be included for better classification but are
inconvenient for conventional methods. Artificial neural networks can handle non-convex decisions. The uses of textural features help to resolve misclassification. This paper describes the design and development of a hierarchical network by incorporating textural features. The effect of inclusion of textual features on classification is also studied.

Item Type: Article
Keywords (uncontrolled): Gray values; neural classifier; supervised classifier; textural features
Research Areas: A. > School of Science and Technology > Design Engineering and Mathematics
Item ID: 11574
Useful Links:
Depositing User: Vaibhav Gandhi
Date Deposited: 20 Aug 2013 10:32
Last Modified: 13 Oct 2016 14:28
URI: http://eprints.mdx.ac.uk/id/eprint/11574

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