Earticle

초록

영어

Grading the fruit by using machine vision system, it is hoped by the computer to recognize and understand the image automatically, in order to achieve this objective, the key step is to capture the suitable fruit images so that fruit image information can be effectively decomposed. Therefore, the final result of decomposition is to get some of the characteristics of each image with its own motifs, such as borders, shape and so on. By using these primitives, you can match a certain pattern, so as to determine the quality of the fruit. In this paper, it takes the overview of the finite element segmentation as a starting point, combined with the interpretation of the numerical algorithm and FCM algorithm functional convergence of the sequence, relying on Mumford-Shah function model to investigate the generation of fruit image finite element model.

목차

Abstract
 1. Introduction
 2. Methods
  2.1. Adaptive Adjustment of Grid
  2.2. Mumford-Shah Pan Function Model
  2.3. FCM Algorithm
 3. The Introduction of FCM Algorithm
  3.1. Introducing Fuzzy Weakening Operator
  3.2. The Generation of Finite Element Model of Image
  3.2. The Introduction of Kohonen Clustering Neural Network Sets the Initial Cluster as Center
 4. Conclusion
 References

키워드

저자

• Li Han [ College of Computer and Communication Engineering,Zhengzhou University of LightIndustry ]
• Pengyuan Wang [ College of Computer and Communication Engineering,Zhengzhou University of LightIndustry ]

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