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Image Classification based on Subset Feature set and Optimized by Local Hill climbing Method

International Journal of Computer Applications
© 2012 by IJCA Journal
Volume 43 - Number 11
Year of Publication: 2012
Preeti Choudhary
Nishchol Mishra

Preeti Choudhary and Nishchol Mishra. Article: Image Classification based on Subset Feature set and Optimized by Local Hill climbing Method. International Journal of Computer Applications 43(11):1-4, April 2012. Full text available. BibTeX

	author = {Preeti Choudhary and Nishchol Mishra},
	title = {Article: Image Classification based on Subset Feature set and Optimized by Local Hill climbing Method},
	journal = {International Journal of Computer Applications},
	year = {2012},
	volume = {43},
	number = {11},
	pages = {1-4},
	month = {April},
	note = {Full text available}


Image classification is a very challenging and important problem in the image management and retrieval system. The traditional methods are not effective to the image classification due to the high dimensionality of the image feature space. This paper proposes a method of image classification over a given data set using subset feature set and morphological profile. On the basis of subset feature set the image data set are classified. The input is the image and the result is the class of images related to that image. Using this technique, the performance is found to be 84%, which is quite acceptable.


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