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Abstract            Volume:4  Issue-7  Year-2016         Original Research Articles


Online ISSN : 2347 - 3215
Issues : 12 per year
Publisher : Excellent Publishers
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Mathematical Modeling of Content Based Image Classification Techniques for Artificial Vision
Rajashri Mahajan* and S.V. Patil
E & TC Department, J.T. Mahajan College of Engineering, Faizpur, India
*Corresponding author
Abstract:

Recent years have seen a rapid increase in the size of digital image collections. Any advance in our ability to organize unlabelled images according to their semantic content is a very useful step in managing these collections. Image is a collection of row and column that is called pixel values. Extracting best matched image from large collection of database is emerging task. Image retrieval is mainly used in image processing, pattern recognition and computer vision. CBIR technique used in many areas such as medical, academic, art, fashion, entertainment. Generally image have colour, texture, shape and size are relevant feature so extract all the relevant and irrelevant features of image. After extracting all the feature of image applies SVM i.e. supervised learning algorithm get optimal result for image classification.

Keywords: CBIR, Image Retrieval, SVM, Image classification, image processing, pattern recognition, computer vision.
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How to cite this article:

Rajashri Mahajan and S.V. Patil. 2016. Mathematical Modeling of Content Based Image Classification Techniques for Artificial Vision.Int.J.Curr.Res.Aca.Rev. 4(7): 114-124
doi: http://dx.doi.org/10.20546/ijcrar.2016.407.015
Copyright: This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-ShareAlike license.