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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Esen, E. Ozkan, S. Atil, I. Arabaci, M.A. Tankiz, S. |
| Copyright Year | 2014 |
| Description | Author affiliation: TUBITAK UZAY Image Process. Group, METU Balgat, Ankara, Turkey (Esen, E.; Ozkan, S.; Atil, I.; Arabaci, M.A.; Tankiz, S.) |
| Abstract | In this work, we propose a novel community detection method that is specifically designed for image communities. We define image community as a coherent subgroup of images within a large set of images. In order to detect image communities, we construct an image graph by utilizing visual affinity between each image pair and then prune most of the links. Instead of affinity values, we prefer ranking of neighboring images and get rid of range mismatch of affinity values. The resulting directed graph is processed to detect the image communities by using the proposed deterministic method. The proposed method is compared against state-of-the-art community detection methods that can operate on directed graphs. In the experiments, we use various sets of images for which ground truths are determined manually. The results indicate that our method significantly outperforms the compared state-of-the-art methods. Furthermore, the proposed method appears to have a consistent performance between sets unlike the compared methods. We believe that the proposed community detection method can be successfully utilized in many different applications. |
| Sponsorship | IEEE |
| Starting Page | 1 |
| Ending Page | 4 |
| File Size | 2967208 |
| Page Count | 4 |
| File Format | |
| ISBN | 9781479939909 |
| ISSN | 19493991 |
| DOI | 10.1109/CBMI.2014.6849841 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2014-06-18 |
| Publisher Place | Austria |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Measurement Computers Visualization Image edge detection Communities Detection algorithms Equations |
| Content Type | Text |
| Resource Type | Article |
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