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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Yue Li Chia-Hung Wei |
| Copyright Year | 2011 |
| Description | Author affiliation: Department of Information Management, Ching Yun University, Taiwan (Chia-Hung Wei) || College of Software, Nankai University, China (Yue Li) |
| Abstract | This report proposes a hierarchical correlation calculation approach to content-based mammogram retrieval. In this approach, images are represented as a Gaussian pyramid with several reduced- resolution levels. A global search is first conducted to identify the optimal matching position, where the correlation between the query image and the target images in the database is maximal. Local search is performed in the region comprising the four child pixels at a higher resolution level in order to locate the position with maximal correlation at greater resolution. Finally, this position with the maximal correlation found at the finest resolution level is used as the image similarity measure for retrieving images. Experimental results have shown that this approach achieves 59% in precision and 54% in recall when the threshold of correlation is ≥ 0.5. |
| Starting Page | 550 |
| Ending Page | 553 |
| File Size | 297940 |
| Page Count | 4 |
| File Format | |
| ISBN | 9781612847719 |
| e-ISBN | 9781612847740 |
| DOI | 10.1109/ICMT.2011.6002137 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2011-07-26 |
| Publisher Place | China |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Performance evaluation Correlation Image resolution Filtering Image retrieval Content-Based Image Retrieval Mammogram Optimal matching Image Pyramids |
| Content Type | Text |
| Resource Type | Article |
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