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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Paris, S. |
| Copyright Year | 2009 |
| Abstract | In Content Based Image Retrieval (CBIR), images are segmented to synthesize image information. Among several characteristics like color or edges, texture is useful for segmenting. This paper proposes an intensive multiresolution approach to texture segmentation based on a wavelet transform. The technique delivers schematic descriptions of images. That is to say, it provides the main regions of interest (ROIs) according to image information. Firstly, the process divides images into 2 × 2 blocks. Then, it tracks texture through the multiresolution offered by the wavelet transform to form featuring vectors. Next, a K-means algorithm partitions the texture vector space into clusters. Finally, a connected component extraction delivers the image schema. |
| Starting Page | 22 |
| Ending Page | 27 |
| File Size | 785122 |
| Page Count | 6 |
| File Format | |
| ISBN | 9781424436835 |
| DOI | 10.1109/INTENSIVE.2009.16 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2009-04-20 |
| Publisher Place | Spain |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Wavelet transforms Content based retrieval color Image retrieval texture Multimedia databases Information retrieval Data mining Image segmentation Image databases Layout CBIR wavelet intensive schematization Pixel |
| Content Type | Text |
| Resource Type | Article |
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