Flower Classification using Texture and Color Features

6 pages•Published: June 12, 2017

Riddhi Shaparia, Narendra Patel and Zankhana Shah

Abstract

In this research paper, we have used texture and color features for flower classification. Standard database of flowers have used for experiments. The pre- processing like noise removal and segmentation for elimination of background are apply on input images. Texture and color features are extracted from the segmented images. Texture feature is extracted using GLCM (Gray Level Co-occurrence Matrix) method and color feature is extracted using Color moment. For classification, neural network classifier is used. The overall accuracy of the system is 95.0 %.

Keyphrases: classification, color moment, glcm, neural network

In: Rajkumar Buyya, Rajiv Ranjan, Sumantra Dutta Roy, Mehul Raval, Mukesh Zaveri, Hiren Patel, Amit Ganatra, Darshak G. Thakore, Trupti A. Desai, Zankhana H. Shah, Narendra M. Patel, Mukesh E. Shimpi, Rajiv B. Gandhi, Jagdish M. Rathod, Bhargav C. Goradiya, Mehfuza S. Holia and Dharita K. Patel (editors). ICRISET2017. International Conference on Research and Innovations in Science, Engineering and Technology. Selected Papers in Computing, vol 2, pages 113-118.

Links:	https://easychair.org/publications/paper/jKTm
	https://doi.org/10.29007/6mt1

BibTeX entry

@inproceedings{ICRISET2017:Flower_Classification_using_Texture,
  author    = {Riddhi Shaparia and Narendra Patel and Zankhana Shah},
  title     = {Flower Classification using Texture and Color Features},
  booktitle = {ICRISET2017. International Conference on Research and Innovations in Science, Engineering and Technology. Selected Papers in Computing},
  editor    = {Rajkumar Buyya and Rajiv Ranjan and Sumantra Dutta Roy and Mehul Raval and Mukesh Zaveri and Hiren Patel and Amit Ganatra and Darshak G. Thakore and Trupti A. Desai and Zankhana H. Shah and Narendra M. Patel and Mukesh E. Shimpi and Rajiv B. Gandhi and Jagdish M. Rathod and Bhargav C. Goradiya and Mehfuza S. Holia and Dharita K. Patel},
  series    = {Kalpa Publications in Computing},
  volume    = {2},
  publisher = {EasyChair},
  bibsource = {EasyChair, https://easychair.org},
  issn      = {2515-1762},
  url       = {/publications/paper/jKTm},
  doi       = {10.29007/6mt1},
  pages     = {113-118},
  year      = {2017}}

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