Fuzzy knowledge based enhanced matting

Charles Z. Liu, Manolya Kavakli

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

2 Citations (Scopus)

Abstract

The goal of this paper is to address how to use human experience to develop an enhanced matting strategy. Based on a recursive α optimization framework, we present an adaptive fuzzy learning strategy for enhancement of matting. Taking into account the uncertainty of data, the proposed scheme successfully applies the expert human knowledge into matting. Experimental results are given to demonstrate the effect of the proposed method compared to some classical methods. The results indicate that the proposed adaptive learning algorithm handles uncertain pixels and perform stable matting.

Original languageEnglish
Title of host publicationProceedings of the 2016 IEEE 11th Conference on Industrial Electronics and Applications, ICIEA 2016
Place of PublicationPiscataway, NJ
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Pages934-939
Number of pages6
ISBN (Electronic)9781509026050
DOIs
Publication statusPublished - 19 Oct 2016
Event11th IEEE Conference on Industrial Electronics and Applications, ICIEA 2016 - Hefei, China
Duration: 5 Jun 20167 Jun 2016

Other

Other11th IEEE Conference on Industrial Electronics and Applications, ICIEA 2016
CountryChina
CityHefei
Period5/06/167/06/16

Fingerprint Dive into the research topics of 'Fuzzy knowledge based enhanced matting'. Together they form a unique fingerprint.

  • Cite this

    Liu, C. Z., & Kavakli, M. (2016). Fuzzy knowledge based enhanced matting. In Proceedings of the 2016 IEEE 11th Conference on Industrial Electronics and Applications, ICIEA 2016 (pp. 934-939). [7603716] Piscataway, NJ: Institute of Electrical and Electronics Engineers (IEEE). https://doi.org/10.1109/ICIEA.2016.7603716