Open Access Open Access  Restricted Access Subscription or Fee Access

q-Recursive Method to Improve Accuracy and Time Taken by Content Based Image Retrieval

Nidhi Bansal


Content Based Image Retrieval is an active and fast advancing research area for manipulating large amount of image databases. It is based on extracting and comparing the visual attributes of the images. Examples of visual attributes are color, texture, shape, and motion parameters. In order to extract features of an image, various feature extraction methods are available. One of them is moment description. The Zernike Moment Descriptor is a moment based Shape Descriptor. In this paper, we proposed that the process of Content Based Image Retrieval can be made fast and more accurate by using the q-recursive method to compute Zernike Moments. The method retrieves most relevant images according to the similarity measure calculated between features of the query image and images of the image database.

Full Text:



  • There are currently no refbacks.

Disclaimer/Regarding indexing issue:

We have provided the online access of all issues and papers to the indexing agencies (as given on journal web site). It’s depend on indexing agencies when, how and what manner they can index or not. Hence, we like to inform that on the basis of earlier indexing, we can’t predict the today or future indexing policy of third party (i.e. indexing agencies) as they have right to discontinue any journal at any time without prior information to the journal. So, please neither sends any question nor expects any answer from us on the behalf of third party i.e. indexing agencies.Hence, we will not issue any certificate or letter for indexing issue. Our role is just to provide the online access to them. So we do properly this and one can visit indexing agencies website to get the authentic information.