Title: | Evaluation of fuzzy rough set feature selection for content based image retrieval system with noisy images |
Authors: | Shahabi Lotfabadi, Maryam Fairuz Shiratuddin, Mohd Wai Wong, Kok |
Citation: | WSCG 2014: communication papers proceedings: 22nd International Conference in Central Europeon Computer Graphics, Visualization and Computer Visionin co-operation with EUROGRAPHICS Association, p. 95-102. |
Issue Date: | 2014 |
Publisher: | Václav Skala - UNION Agency |
Document type: | konferenční příspěvek conferenceObject |
URI: | wscg.zcu.cz/WSCG2014/!!_2014-WSCG-Communication.pdf http://hdl.handle.net/11025/26383 |
ISBN: | 978-80-86943-71-8 |
Keywords: | fuzzy hrubá množina;obsah založený na systému načítání obrazu;hluk |
Keywords in different language: | fuzzy rough set;content based image retrieval system;noise |
Abstract in different language: | In this paper Fuzzy Rough Set is used for feature selection in the Content Based Image Retrieval system. Noisy query images are fed to this Content Based Image Retrieval system and the results are compared with four other feature selection methods. The four other feature selection methods are Genetic Algorithm, Information Gain, OneR and Principle Component Analysis. The main objective of this paper is to evaluate the rules which are extracted from fuzzy rough set and determine whether these rules which are used for training the Support Vector Machine can deal with noisy query images as well as the original queried images. To evaluate the Fuzzy Rough set feature selection, we use 10 sematic group images from COREL database which we have purposely placed some defect by adding Gaussian, Poisson and Salt and Pepper noises of different magnitudes. As a result, the proposed method performed better in term of accuracies in most of the different types of noise when compared to the other four feature selection methods. |
Rights: | @ Václav Skala - UNION Agency |
Appears in Collections: | WSCG 2014: Communication Papers Proceedings |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
Lotfabadi.pdf | Plný text | 974,73 kB | Adobe PDF | View/Open |
Please use this identifier to cite or link to this item:
http://hdl.handle.net/11025/26383
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.