A Survey on Feature Analysis and Classification for Image Annotation using Saliency Map

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Sayali Suryawanshi, Antara Bhattacharya

Abstract

With the advances in multimedia technologies collections of digital images is growing rapidly. Due to the popularity of various digital cameras and the rapid growth of social media tools, internet based photo sharing have increase in daily life. As the database have huge amount of images and other files, it is difficult to retrieve the required images. Supervised dictionary learning feature based image retrieval is very important area of research in the field of image retrieval. The feature based image annotation paradigm aims to tackle the automated image annotation by exploiting feature based image retrieval. Aim of this research work is to extract features related to the image in the form of annotation and develop system for clustering of data user define clusters with the help of image processing. To solve the problem of data classification into large dataset, to get an efficient system which classify data not only on basis of the dataset but also on basis of the image specified class.

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How to Cite
, S. S. A. B. (2016). A Survey on Feature Analysis and Classification for Image Annotation using Saliency Map. International Journal on Recent and Innovation Trends in Computing and Communication, 4(1), 52–55. https://doi.org/10.17762/ijritcc.v4i1.1707
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