Computer Science ›› 2019, Vol. 46 ›› Issue (2): 286-293.doi: 10.11896/j.issn.1002-137X.2019.02.044

• Graphics ,Image & Pattern Recognition • Previous Articles     Next Articles

Mismatch Elimination Algorithm Based on Point Line Feature Fusion

WEI Yu-hui1, WANG Yong-jun2, WANG Guo-dong1, LIU Hong-min2, WANG Jing2   

  1. School of Physics and Electronic Information,Henan Polytechnic University,Jiaozuo,Henan 454000,China1
    School of Computer Science and Technology,Henan Polytechnic University,Jiaozuo,Henan 454000,China2
  • Received:2018-01-26 Online:2019-02-25 Published:2019-02-25

Abstract: Image feature matching plays an important role in computer vision,the feature point matching technology based on descriptors have made a series of achievements,since curves have different lengths,incorrect position of endpoints and contain lots of relative texture around neighbor,the research of feature curve matching is still a challenging topic,and many curve matching methods have the problem of fewer matches and low accuracy of feature matching.To improve the total number and accuracy of feature matching,this paper proposed a novel Point Line feature Fusion (PLF) algorithm based on the location relationship between feature points and feature curves.Firstly,it defines the distance from a point to a curve,and obtains the matched points and curves using point and curve descriptors respectively from the images.Secondly,it determines the matched point pairs in the support areas of one pair of matched curves,and eliminate the mismatch of curves according to the distance constraints between the obtained matched points and the curve.Then,it removes the mismatch of points according to the distance constraint between the point and the curve.Three combinations of points and curves have been used in the experiment,which are the points extracted by SIFT and the curves extracted by IOCD curve descriptor,the points extracted by SIFT and the curves extracted by IOMSD curve descriptor,the points extracted by SIFT and the curves extracted by GOCD curve descriptor.The method hasapplicabi-lity to many kinds of point and curve descriptors,it is not only suitable for the points and curves,but also for points and lines,it has applicability to many kinds of features.Experimental results show that the proposed algorithm can effectively improve the total number and accuracy of feature matching,and also increase the accuracy of point matching under image rotation,viewpoint change,illumination change,JPEG compression,noise and image blur.

Key words: Curve matching, Distance constraints, PLF algorithm, Point line feature fusion, Point matching

CLC Number: 

  • TP391
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