Paper Info
Title
Experimental analogy of different texture feature extraction techniques in image retrieval systems
Abstract
Content based image retrieval (CBIR) is an extrusive technique of retrieving the relevant images from vast image archives by extracting their low level features. In this research paper, the pursuance of five most prominent texture feature extraction techniques used in CBIR systems are experimentally compared in detail. The main issue with the CBIR systems is the proper selection of techniques for the extraction of low level features which comprises of color, texture and shape. Among these features, texture is one of the most decisive and dominant features. This selection of features completely depends upon the type of images to be retrieved from the database. The texture techniques explored here are Grey level co-occurrence matrix (GLCM), Discrete wavelet transform (DWT), Gabor transform, Curvelet and Local binary pattern (LBP). These are experimented on three touchstone databases which are Wang, Corel-5 K and Corel-10 K. The chief parameters of CBIR systems are evaluated here such as precision, recall and F-measure on all these databases using all the techniques. After detailed investigation it is figured out that LBP, GLCM and DWT provide highlighted and comparable results in all these datasets in terms of average precision. Besides practical implementation, the precised conceptual examination of these three texture techniques is also proposed in this article. So, this analysis is extremely beneficial for selecting the appropriate feature extraction technique by taking into consideration the experimental results along with image conditions such as noise, rotation etc.
Year
DOI
Venue
2020
10.1007/s11042-020-09317-3
MULTIMEDIA TOOLS AND APPLICATIONS
Keywords
DocType
Volume
Discrete wavelet transform,Local binary pattern,Precision,F-measure,Relevance feedback,Recall
Journal
79.0
Issue
ISSN
Citations 
37-38
1380-7501
0
PageRank 
References 
Authors
0.34
0
2
Name
Order
Citations
PageRank
Shefali Dhingra101.35
Poonam Bansal202.03