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

Article

Shah, S. and Gandhi, V. 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.
TypeArticle
TitleImage classification based on textural features using Artificial Neural Network (ANN)
AuthorsShah, S. and Gandhi, V.
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.

KeywordsGray values; neural classifier; supervised classifier; textural features
PublisherSpringer
JournalJournal of The Institution of Engineers (India): Series A
ISSN2250-2149
Publication dates
PrintJan 2004
Publication process dates
Deposited20 Aug 2013
Output statusPublished
Web address (URL)http://www.springer.com/engineering/civil+engineering/journal/40030
LanguageEnglish
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