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A Survey on Image Mining, its Techniques and Application

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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Year of Publication: 2016
Authors:
Vaibhavi S. Shukla, Jay Vala
10.5120/ijca2016907978

Vaibhavi S Shukla and Jay Vala. Article: A Survey on Image Mining, its Techniques and Application. International Journal of Computer Applications 133(9):12-15, January 2016. Published by Foundation of Computer Science (FCS), NY, USA. BibTeX

@article{key:article,
	author = {Vaibhavi S. Shukla and Jay Vala},
	title = {Article: A Survey on Image Mining, its Techniques and Application},
	journal = {International Journal of Computer Applications},
	year = {2016},
	volume = {133},
	number = {9},
	pages = {12-15},
	month = {January},
	note = {Published by Foundation of Computer Science (FCS), NY, USA}
}

Abstract

We know that today’s world is digital world and we have use digital data such as video, audio, images etc. in various fields for various purposes. In present scenario, image plays vital role in every aspect of business such as business images, satellite images, and medical images and so on. Image mining is challenging field which extends traditional data mining from structured data to unstructured data such as image data. The main aim of this paper is to present a survey of the various techniques used for image mining applications. Forests fires are a significant problem. To fight against these disasters, the accurate prediction of forest fire is a crucial issue. The increase in the number of forest fires in the last few years has forced governments to take precautions. If the fire fighters know where the fire will be in sometimes it would be easier for them to stop the fire. Therefore a big need for predicting the fire behavior exists. In this paper various techniques of image mining and different algorithms used to analyze a key event –fire is studied. This paper covers literature survey of image mining techniques and its applications.

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Keywords

Data mining, Multimedia mining, Image mining, forest fire