Earticle

초록

영어

The accurate segmentation and extraction of bamboo cross-section image has a vital role on bamboo processing automation. The Lab color space in accordance with the color features of the bamboo wood cross-section is chosen in this paper. The bamboo cross-section image segmentation and extraction algorithm based on the clustering theory is proposed. The algorithm firstly takes advantage of the character that the colors represented by channel a and channel b of the Lab color space accord with the color of the bamboo wood, to be combined feature vector. Then the algorithm uses the k-mean clustering algorithm to classify the eigenvectors to realize the segmentation of the bamboo wood cross-section. At last the circle fitting algorithm is used to realize the final frame of the bamboo wood cross-section. The results of the experiments show that the algorithm can be used to realize the complete segmentation of the cross-section image of bamboo wood, and to frame the results correctly, the time performance of which can meet the requirements of the subsequent processing.

목차

Abstract
 1. Introduction
 2. Color Space and Transformation
 3. Research on the Bamboo Image Segmentation Algorithm
  3.1 Feature Extraction based on Lab Color Space
  3.2 Bamboo Wood Cross-section Image Segmentation and Circle Fitting Frame Algorithm
 4. The Experiment and Result Analysis
 5. Conclusion
 ACKNOWLEDGEMENTS
 References

키워드

저자

• WANG Hai-feng [ Information and Computer Engineering College, Northeast Forestry University, Harbin, 150040, P.R. China; School of Electronic and Information Engineering, Qiongzhou University, Sanya, Hainan, 572022, P.R. China ]
• REN Hong-e [ Information and Computer Engineering College, Northeast Forestry University, Harbin, 150040, P.R. China ]

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