Semantic modelling of unshaped object: An efficient approach in content based image retrieval

Author

Shamsujjoha, Md ; Ahmed, Md Shakil ; Hossain, Fahmida ; Jabid, Taskeed

Author_Institution

Dept. of Comput. Sci. & Eng., East West Univ., Dhaka, Bangladesh

fYear

2014

Firstpage

30

Lastpage

34

Abstract

This paper presents an efficient image exploration scheme for the unshaped object using semantic modelling. The local regions of an image have been classified with respect to the frequency of occurrences. The semantic concept is evaluated using RGB histogram dissimilarity factor, overall dissimilarity factor and regional dissimilarity factor. The dissimilarities determine the local concept with accuracy up to 89.86% which is much higher than the existing techniques. The proposed algorithm also allows to ranks the unshaped objects according to their semantic similarity.

Keywords

content-based retrieval; image classification; image colour analysis; image retrieval; RGB histogram dissimilarity factor; content based image retrieval; image exploration scheme; local concept; local image region classification; occurrence frequency; overall dissimilarity factor; regional dissimilarity factor; semantic modelling; semantic similarity; unshaped object ranking; Accuracy; Computational modeling; Computers; Conferences; Histograms; Image color analysis; Semantics; Content based image retrieval; Dissimilarity factors; Histogram; Semantic modeling; Unshaped object;

fLanguage

English

Publisher

ieee

Conference_Titel

Computer and Information Technology (ICCIT), 2014 17th International Conference on

Type

conf

DOI

10.1109/ICCITechn.2014.7073070

Filename

7073070