Title :
A Novel Graph-Based Image Annotation Refinement Algorithm
Author_Institution :
Sch. of Comput. Sci. & Technol., Shandong Economic Univ., Ji´´nan, China
Abstract :
A novel graph-based approach to automatically refine image annotation is presented in this paper. Given an unannotated image, a set of candidate annotations is extracted by the existing image annotation method. Then, each candidate annotation is converted to vertex of a graph and the semantic similarity between two candidate annotations is used as edge weight. Next, a heuristics graph algorithm solving weighted MAX-CUT problem is used to prune the noisy annotations. Experimental results demonstrate the effectiveness of our image annotation refinement algorithm.
Keywords :
content-based retrieval; graph theory; image processing; image retrieval; graph based image annotation refinement algorithm; graph vertex; heuristics graph algorithm; semantic similarity; weighted MAX-CUT problem; Approximation algorithms; Computer science; Content based retrieval; Fuzzy systems; Heuristic algorithms; Humans; Image analysis; Image converters; Image retrieval; Indexing; Image annotation refinement; MAX-CUT problem; graph algorithm; semantic similarity;
Conference_Titel :
Fuzzy Systems and Knowledge Discovery, 2009. FSKD '09. Sixth International Conference on
Conference_Location :
Tianjin
Print_ISBN :
978-0-7695-3735-1
DOI :
10.1109/FSKD.2009.369
