earticle

논문검색

Fractional Differentiation-based Image Feature Extraction

초록

영어

Two novel methods for image feature extraction based on fractional differentiation are presented in this paper. The first method is the feature extraction of fusing multi-direction CRONE operators. In this method, the fractional differential CRONE mask is generalized to eight directions at first for extracting image features; then the extracted features are tested by the statistic method and fused by the gradient ratio, so that the outlines of the objects in the image are obtained. In order to extract the detail feature information in the image effectively, the second method, the ‘S+Z’ extraction combined with the space-filling curves, is presented. By introducing the space-filling curves, the ‘S’ curve and the ‘Z’ curve, and making full use of the neighborhood information of image pixels, the detailed features of the objects in the image are obtained. The experiment results show that our methods can obtain satisfactory image features.

목차

Abstract
 1. Introduction
 2. Multi-direction Feature Extraction based on CRONE Operator
  2.1 CRONE Operator
  2.2 Multi-direction Feature Extraction 
  2.3 Feature Test
 3. CRONE Operator based ‘S+Z’ Extraction Method
  3.1 'S' Curve based New Mask
  3.2 The Improvement of the 'S' Mask
 4. Experimental Analysis
 5. Conclusions
 Acknowledgments
 References

저자정보

  • Xiangwei Xu School of Science, Xi'an University of Technology, Xi'an, China
  • Fang Dai School of Science, Xi'an University of Technology, Xi'an, China
  • Jianmin Long Deapartment of Engineering Mechanics, SVL, Xi'an Jiaotong University, Xi'an, China
  • Wenyan Guo School of Science, Xi'an University of Technology, Xi'an, China

참고문헌

자료제공 : 네이버학술정보

    함께 이용한 논문

      ※ 원문제공기관과의 협약기간이 종료되어 열람이 제한될 수 있습니다.

      0개의 논문이 장바구니에 담겼습니다.