Computer Science ›› 2019, Vol. 46 ›› Issue (7): 263-267.doi: 10.11896/j.issn.1002-137X.2019.07.040

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

Enhanced Rotation Invariant LBP Algorithm and Its Application in Image Retrieval

SUN Wei,ZHAO Yu-pu   

  1. (School of Information and Control Engineering,China University of Mining and Technology,Xuzhou,Jiangsu 221000,China)
  • Received:2018-05-25 Online:2019-07-15 Published:2019-07-15

Abstract: CBIR (Content-based image retrieval) is a hot topic in image retrieval.LBP texture features are commonly used in CBIR.When the classic LBP algorithm is applied to the image retrieval system,the retrieval efficiency is low,and it does not have the characteristics of rotation invariance.Although the rotation invariant LBP (LBPri) algorithm has the characteristics of rotation invariance,its retrieval efficiency is low.In order to improve the precision and efficiency of CBIR,based on the classical LBP algorithm,this paper proposed an enhanced rotation invariant LBP descriptor (ELBPri).Firstly,the ELBPri descriptor extracts the Harris corners from the original grayscale,and then samples the original grayscale in the center of the Harris corners.Secondly,ELBPri descriptor encodes the sampled image in rotation invariant LBP.Thirdly,the LBP histograms of each image are counted.Finally,ELBPri descriptor calculates the Eucli-dean distance between the LBP histograms of the images and sort them according to similarity.Experimental results show that compared with LBPri descriptor,the average precision of the ELBPri descriptor used in the retrieval of gene-ral texture image sets by the CBIR system is increased by 5.64%,and the average query time is shortened by 0.4ms.The average precision is increased by 5.94% when retrieving rotation texture image sets,and the average query time is shortened by 0.12ms.

Key words: Content-based image retrieval, ELBPri descriptor, Euclidean distance, Harris algorithm, LBP pseudo grayscale

CLC Number: 

  • TP391
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