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Author:

Ma, H.-B. (Ma, H.-B..) | Zhang, P.-C. (Zhang, P.-C..) | Zhang, Q. (Zhang, Q..) | Yang, G.-R. (Yang, G.-R..) | Wang, N. (Wang, N..) | Gui, Z.-G. (Gui, Z.-G..)

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Scopus PKU

Abstract:

Scale invariant feature transform (SIFT) is a local feature descriptor that searches from extreme points in spatial scales. Aiming at the speeding up the matching process of the traditional Scale-invariant Feature Transform (SIFT) algorithm, a fast image matching method based on improved SIFT is proposed. It eliminates some invalid feature points by calculating the two-dimensional entropy of feature points. in the feature extraction stage, eliminating the feature points with larger two-dimensional entropy. In the feature point matching stage, a reliable matching pair is found by traversing the difference of two-dimensional entropy between a feature point of the reference image and a feature point of the image to be matched. this will reduce the computation of Euclidean distance in matching process. The experimental results show that the improved algorithm has a capacity to effectively improve the image matching speed on the premise of maintaining stability, and it is 1.6 times as much as the original matching speed. © 2019, The Press of NUC. All right reserved.

Keyword:

Euclidean distance; Feature point screening; Image matching; SIFT; Two-dimensional entropy

Author Community:

  • [ 1 ] [Ma, H.-B.]Shanxi Provincial Key Laboratory for Biomedical Imaging and Big Data, North University of China, Taiyuan, 030051, China
  • [ 2 ] [Zhang, P.-C.]Shanxi Provincial Key Laboratory for Biomedical Imaging and Big Data, North University of China, Taiyuan, 030051, China
  • [ 3 ] [Zhang, Q.]Shanxi Provincial Key Laboratory for Biomedical Imaging and Big Data, North University of China, Taiyuan, 030051, China
  • [ 4 ] [Yang, G.-R.]School of Information and Communication Engineering, Beijing University of Technology, Beijing, 100124, China
  • [ 5 ] [Wang, N.]Shanxi Provincial Key Laboratory for Biomedical Imaging and Big Data, North University of China, Taiyuan, 030051, China
  • [ 6 ] [Gui, Z.-G.]Shanxi Provincial Key Laboratory for Biomedical Imaging and Big Data, North University of China, Taiyuan, 030051, China

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Source :

Journal of North University of China (Natural Science Edition)

ISSN: 1673-3193

Year: 2019

Issue: 1

Volume: 40

Page: 63-69

Cited Count:

WoS CC Cited Count: 0

SCOPUS Cited Count: 2

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 0

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