Fractals Based Clustering for CBIR

Journal Title: International Journal on Computer Science and Engineering - Year 2012, Vol 4, Issue 6

Abstract

Fractal based CBIR is based on the self similarity fundamentals of fractals. Mathematical and natural fractals are the shapes whose roughness and fragmentation neither tend to vanish, nor fluctuate, but remain essentially unchanged as one zooms in continually and examination is refined. Since an image can be characterized by its fractal code, a fractal code can therefore be used as a signature of the image. Image clustering supports the hypothesis that semantically similar images tend to be clustered in some feature space. The meaningful clustering is in pursuit of search for nearest neighbor in terms of similarity of the images. The objective of this work is to evaluate the use of fractal dimension as a quantitative index and effectiveness of clustering approach for image retrieval mechanism. The image retrieval mechanism has been implemented using clustering and Hausdorff dimension based fractals so as to combine the advantages of both the approaches. The results are encouraging enough to investigate use of fractals for CBIR.

Authors and Affiliations

Suhas Rautmare , Anjali Bhalchandra

Keywords

Related Articles

AI based Digital Companding Scheme for OFDM system using custom constellation Mapping and selection

Data rate is important in telecommunication because it is irectly proportional to the cost of transmitting the signal. Saving bits is the same as saving money . In this paper we propose new digital companding scheme for...

A Comparative Study for Deblured Average Blurred Images

This paper attempts to undertake the study of Restored Average Blurred Images. by using three types of techniques of deblurring image as Wiener filter, Regularized filter and Lucy Richardson deconvlutoin algorithm with a...

Software efforts estimation using Use Case Point approach by increasing Technical Complexity and Experience Factors

An IT industry wants a simple and accurate method of efforts estimation. Estimation of efforts before starting of work is a prediction and prediction always not accurate. Intermediate COCOMO considered 17 factor that aff...

A survey on Data Storage and Retrieval in Cloud Computing

This paper presents the survey on data storage and retrieval in cloud computing. In this paper the study on scope and security issues related to data storage and information retrieval in cloud computing is done. Data sto...

Multi-document Summarization for Query Answering E-learning System

The proposed E-learning system aims at providing a multi-document summarization for documents retrieved from Google and providing the user a precise answer for his/her query under the domain of “Operating Systems”. This...

Download PDF file
  • EP ID EP150858
  • DOI -
  • Views 131
  • Downloads 0

How To Cite

Suhas Rautmare, Anjali Bhalchandra (2012). Fractals Based Clustering for CBIR. International Journal on Computer Science and Engineering, 4(6), 1007-1016. https://europub.co.uk/articles/-A-150858