Title :
Image community detection
Author :
Esen, Ersin ; Ozkan, Savas ; Atil, I. ; Arabaci, M.A. ; Tankiz, Seda
Author_Institution :
TUBITAK UZAY, Ankara, Turkey
Abstract :
In this work, we propose a new method which can detect image communities inside an image set. The proposed method differs from previous works by representing image relations with directed graphs and performing community analysis on these directed graphs. By analyzing resulting image communities, we can observe the robustness of the proposed method against image deformations (e.g. cutting, text overlay, color changes). The proposed method can be applied to text-based image search results to achieve content-based image search. We believe that the proposed method can be successfully used to bridge the gap between available text-based methods and content-based image search.
Keywords :
content-based retrieval; directed graphs; image classification; image retrieval; color changes; community analysis; content-based image search; directed graphs; image community detection; image deformations; image set; text overlay; text-based image search; Communities; Computer vision; Conferences; Pattern analysis; Signal processing; Transmission line matrix methods; community detection; content-based; directed graph anaysis; image search;
Conference_Titel :
Signal Processing and Communications Applications Conference (SIU), 2014 22nd
Conference_Location :
Trabzon
DOI :
10.1109/SIU.2014.6830335