Co-occurrence of maximal Haar-like wavelet filters for CBIR
by Megha Agarwal; R.P. Maheshwari
International Journal of Signal and Imaging Systems Engineering (IJSISE), Vol. 8, No. 5, 2015

Abstract: This paper introduces a novel technique, co-occurrence of Haar-like wavelet filters (CHLWF), for content-based image retrieval (CBIR). CHLWF obtains correlation among dominant Haar-like wavelet filters to capture structural similarity of images. Selection of dominant Haar-like wavelet filter avoids less prominent directions of intensity variation and reduces complexities of feature computation. Most of the correlogram-based techniques need to decide quantisation thresholds beforehand but CHLWF excludes this as the quantisation is performed automatically based on directions of maximum intensity variations. Performance of proposed feature is justified through three benchmark image databases viz. Corel 1000 (DB1), Brodatz texture (DB2) and MIT VisTex (DB3). Experimental results on DB1 have demonstrated that average precision and average recall are significantly improved by CHLWF in comparison to optimal quantised wavelet correlogram, Gabor wavelet correlogram and cross correlogram (CC). Likewise, on DB2 and DB3 databases, average retrieval rate of CHLWF is better than CC, dual tree complex wavelet transform (DT-CWT), dual tree rotated complex wavelet transform (DT-RCWT) and DT-CWT + DT-RCWT etc. respectively.

Online publication date: Fri, 25-Sep-2015

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

 
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Signal and Imaging Systems Engineering (IJSISE):
Login with your Inderscience username and password:

Username:        Password:          Forgotten your password?

Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email subs@inderscience.com