Earticle

초록

영어

Paddy is the staple food of India and many other countries. It is very essential to find out the best variety that promises good yield. This paper presents a methodology to identify variety of paddy field images. In this work, we have considered 22 varieties of paddy field images and they are divided into three classes based on physical features as light green, lush green and pale green. Identification is done using color, texture and combination of both types of features. Color features are extracted using HSV and texture using GLCM. Artificial Neural network (ANN) is used for identification of variety of paddy field images. Considering only color and texture, the results were not satisfactory. Combined features resulted in n accuracy of 85.7% in light green, 83.1% in lush green and 100% in pale green class. The work is an attempt to disseminate knowledge about new variety of paddy crop required to promote the large scale cultivation.

목차

Abstract
 1. Introduction
 2. Literature Survey
 3. Proposed Method
  3.1 Image Acquisition and Resizing
  3.2 Color and Texture Features Extraction
  3.3. Identification of Paddy Variety
 4. Results and Discussion
 5. Conclusion
 References

키워드

저자

• M. V. Latte [ Principal, JSSATE, Bangalore ]
• Sushila Shidnal [ Assistant Professor, SMVIT, Bangalore ]
• B.S. Anami [ Principal, KLEIT, Hubli ]
• V B Kuligod [ Professor, UAS, Dharwad ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Signal Processing, Image Processing and Pattern Recognition

• 간기

  격월간

• pISSN

  2005-4254

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605