Improving SVM (Support vector Machine) for classification of images based on tree and non-tree images with Neural Network technique for Tree Detection

Authors(2) :-Prof. Divyanshu Rao, Deepti Thakur

This paper compares two different techniques of tree recognition and explains the steps of extracting tree from image, palette formation and conditioning of palette for matching. The focus of the paper is in finding the suitable method for tree recognition on the basis of recognition time, recognition rate, false detection rate, conditioning time, algorithm complexity, bulk detection, database handling. The two methods compared in this paper. Although both methods are practically proven by many researchers, still a comprehensive comparison is missing, we hope the results drawn in this paper will be helpful for the peoples working in same field, the complete algorithm is developed in Matlab for classification of images.

Authors and Affiliations

Prof. Divyanshu Rao
Shri Ram Institute of Technology, Jabalpur, Madhya Pradesh, India
Deepti Thakur
Shri Ram Institute of Technology, Jabalpur, Madhya Pradesh, India

Tree Recognition, SVM (Support Vector Machine), Neural Network, MATLAB

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Publication Details

Published in : Volume 2 | Issue 6 | November-December 2016
Date of Publication : 2016-12-30
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 361-365
Manuscript Number : IJSRSET162690
Publisher : Technoscience Academy

Print ISSN : 2395-1990, Online ISSN : 2394-4099

Cite This Article :

Prof. Divyanshu Rao, Deepti Thakur, " Improving SVM (Support vector Machine) for classification of images based on tree and non-tree images with Neural Network technique for Tree Detection, International Journal of Scientific Research in Science, Engineering and Technology(IJSRSET), Print ISSN : 2395-1990, Online ISSN : 2394-4099, Volume 2, Issue 6, pp.361-365, November-December-2016.
Journal URL : http://ijsrset.com/IJSRSET162690

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