Earticle

초록

영어

Leaves contain important genetic information which can be used as a basis for the identification of plants. As a first step of modeling virtual three-dimensional plant, how to extract visual characteristic information form leaf images has great significance. We propose an optimized C-V model in this paper, which can detect objects in homogeneous regions of given leaf images and speed up running time. The new method combines local information with global information and optimizes the defect that SDF needs to be reconstructed partially so that the energy function is improved. Experimental results show that our algorithm can stop active contours on the correct boundary, get accurate image segmentation, and the speed is more than 1.5 times faster to C-V model.

목차

Abstract
 1. Introduction
 2. C-V Model
 3. The Improved C-V Model for Leaf Images Segmentation
  3.1 Combining with Local Information
  3.2 Internal Energy Functional Term
 4. The Experimental Results
 5. Conclusion
 Acknowledgements
 References

키워드

저자

• Wu Peng [ College of Mechanical and Electronic Engineering, Northeast Forestry University, Harbin, 150040, China ]
• Li Wenlin [ College of Mechanical and Electronic Engineering, Northeast Forestry University, Harbin, 150040, China ]
• Song Wenlong [ College of Mechanical and Electronic Engineering, Northeast Forestry University, Harbin, 150040, China ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of u- and e- Service, Science and Technology

• 간기

  격월간

• pISSN

  2005-4246

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605