Please use this identifier to cite or link to this item:
|Title:||Image cassification: Are rule-based systems effective when classes are fixed and known?||Authors:||Shivakumara, P.
|Issue Date:||2008||Citation:||Shivakumara, P.,Rajan, D.,Sadananthan, S.A. (2008). Image cassification: Are rule-based systems effective when classes are fixed and known?. Proceedings - International Conference on Pattern Recognition. ScholarBank@NUS Repository.||Abstract:||In this paper, we investigate if rule-based systems are useful for image classification problems when the number of classes is fixed. The rules are derived from simple edge features such as width and straightness. A class representative is calculated for each class according to the average percentage of edges that satisfy the rule for a particular class. This percentage for an unknown image is compared to the class representative to assign a label to it. The proposed system does not require extensive feature extraction and classification techniques. It is shown that the rule based system outperforms some of the reported results on scene classification. © 2008 IEEE.||Source Title:||Proceedings - International Conference on Pattern Recognition||URI:||http://scholarbank.nus.edu.sg/handle/10635/41592||ISBN:||9781424421756||ISSN:||10514651|
|Appears in Collections:||Staff Publications|
Show full item record
Files in This Item:
There are no files associated with this item.
checked on Apr 20, 2019
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.