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

Authors

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

Keywords:

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

Abstract

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.

References

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International Journal of Scientific Research in Science, Engineering and Technology

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Published

2016-12-30

Issue

Volume 2, Issue 6, November-December-2016

Section

Research Articles

License

Copyright (c) IJSRSET

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

[1]
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.