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Time series quanslet: A novel primitive for image classification

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

successful indexing/categorization of images greatly enhance the performance of content based retrieval systems by filtering out irrelevant classes. This rather difficult problem has not been adequately addressed in current image database systems. In this paper we have introduced a novel feature for classification of image data by taking the one dimensional representation of it (time series) as our input data. Here we have chosen local shape feature instead of global shape feature for the said purpose which enhances its consistency in case of distorted and mutilated shapes.

Original languageEnglish
Title of host publicationContemporary Computing - 5th International Conference, IC3 2012, Proceedings
Pages64-72
Number of pages9
DOIs
Publication statusPublished - 2012
Event5th International Conference on Contemporary Computing, IC3 2012 - Noida, India
Duration: 06-08-201208-08-2012

Publication series

NameCommunications in Computer and Information Science
Volume306 CCIS
ISSN (Print)1865-0929

Conference

Conference5th International Conference on Contemporary Computing, IC3 2012
Country/TerritoryIndia
CityNoida
Period06-08-1208-08-12

All Science Journal Classification (ASJC) codes

  • General Computer Science
  • General Mathematics

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