Image matching algorithm based on Agast-Adaboost

Journal of Lanzhou University of Technology ›› 2020, Vol. 46 ›› Issue (4): 110-115.

• Automation Technique and Computer Technology • Previous Articles Next Articles

Image matching algorithm based on Agast-Adaboost

XU Zhu-ye¹, ZHAO Xiao-qiang^1,2,3

1. College of Electrical and Information Engineering, Lanzhou Univ. of Tech., Lanzhou 730050, China;
2. Key Laboratory of Gansu Advanced Control for Industrial Processes, Lanzhou Univ. of Tech., Lanzhou 730050, China;
3. National Experimental Teaching Center of Electrical and Control Engineering, Lanzhou Univ. of Tech., Lanzhou 730050, China

Received:2019-04-03 Online:2020-08-28 Published:2020-11-10

Abstract

Abstract: In response to the problem of high mismatch rate and low match rate of traditional floating-point feature description algorithm,a algorithm of ALBFMA (Agast-Adaboost local binary feature matching algorithm, ALBFMA) based on AGAST and fast feature extraction is proposed in this paper. Firstly, this algorithm builds Gaussian scale space pyramid and integrates AGAST with scale space and extracts relevant feature points. Then it uses the improved Adaboost algorithm to conduct binary description for those feature points to generate the feature vector, thus providing a high matching rate and matching accuracy of the algorithm. Our experimental results show that compared with the existing algorithms, the proposed algorithm has advantages of high matching accuracy, and have good robustness for lighting, scale and rotation.

Key words: image matching, scale space, Adaboost, local binary feature

CLC Number:

TP751.1

XU Zhu-ye, ZHAO Xiao-qiang. Image matching algorithm based on Agast-Adaboost[J]. Journal of Lanzhou University of Technology, 2020, 46(4): 110-115.

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Image matching algorithm based on Agast-Adaboost

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