alexa Feature Fusion Based Cartoon Character Retrieval Using
ISSN ONLINE(2319-8753)PRINT(2347-6710)

International Journal of Innovative Research in Science, Engineering and Technology
Open Access

Like us on:
OMICS International organises 3000+ Global Conferenceseries Events every year across USA, Europe & Asia with support from 1000 more scientific Societies and Publishes 700+ Open Access Journals which contains over 50000 eminent personalities, reputed scientists as editorial board members.

Open Access Journals gaining more Readers and Citations

700 Journals and 15,000,000 Readers Each Journal is getting 25,000+ Readers

This Readership is 10 times more when compared to other Subscription Journals (Source: Google Analytics)

Special Issue Article

Feature Fusion Based Cartoon Character Retrieval Using Semi-Msl

J.Ida princess1, V.Nithya1, P.Arjun2
  1. UG Student, University College of Engineering, Villupuram, India.
  2. Assistant Professor, University College of Engineering, Villupuram, India.
Related article at Pubmed, Scholar Google


Cartoon is popular and successful media in our life, its creation is usually of high cost and labor intensive. The computer assisted systems are designed to reduce the time cost of the cartoon production and to develop novel systems that can synthesize new cartoons by reusing existing cartoon materials. For that purpose, we propose a method for cartoon character retrieval with two applications, namely content based cartoon image retrieval and cartoon clip synthesis. In order to retrieve similar cartoon characters two issues are considered. The first issue is how to represent the cartoon characters. The color histogram, hausdorff edge feature, skeleton features and curvature scale space are used to represent the color, shape and gesture of the cartoon characters. The second issue is to combine these features using semi-supervised multi-view subspace learning algorithm. This algorithm uses patch alignment framework to construct and align local patches. Aligned patches have high dimension, it is not efficient to retrieve similar character. In order to improve the efficiency, alternating optimization is utilized for reducing high to low dimensional subspace. Within that space similar characters can be retrieved. This method is useful for animators and cartoon enthusiasts to effectively create new animations.


Share This Page

Additional Info

Loading Please wait..
Peer Reviewed Journals
Make the best use of Scientific Research and information from our 700 + peer reviewed, Open Access Journals
International Conferences 2017-18
Meet Inspiring Speakers and Experts at our 3000+ Global Annual Meetings

Contact Us

© 2008-2017 OMICS International - Open Access Publisher. Best viewed in Mozilla Firefox | Google Chrome | Above IE 7.0 version