Automatic image annotation refinement using fuzzy inference algorithms

DOI

10.2991/ifsa-eusflat-15.2015.205How to use a DOI?

Keywords

Automatic image annotation, annotation re-finement, fuzzy knowledge representation scheme, fuzzy inference algorithms.

Abstract

Facilitating tasks such as image search is one of the goals of image annotation methods that automatically assign keywords to images. In order to achieve as accu-rate annotation on object level as possible, and to reduce negative influence of misclassified objects on the infer-ence of scenes, a knowledge based refinement of object classification results is proposed. A fuzzy knowledge representation scheme called KRFPNr is used to repre-sent knowledge about objects and their relations. Fuzzy inheritance and intersection algorithms are used to refine the image annotation on object level by discarding or replacing object labels that do not fit the context.

Copyright

© 2015, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Marina Ivašic-Kos
AU  - Miran Pobar
AU  - Slobodan Ribari
PY  - 2015/06
DA  - 2015/06
TI  - Automatic image annotation refinement using fuzzy inference algorithms
BT  - Proceedings of the 2015 Conference of the International Fuzzy Systems Association and the European Society for Fuzzy Logic and Technology
PB  - Atlantis Press
SP  - 1446
EP  - 1451
SN  - 1951-6851
UR  - https://doi.org/10.2991/ifsa-eusflat-15.2015.205
DO  - 10.2991/ifsa-eusflat-15.2015.205
ID  - Ivašic-Kos2015/06
ER  -