Image Retrieval using Fractal Feature
碩士 === 義守大學 === 資訊工程學系 === 92 === Content-based image retrieval (CBIR) has attracted many researchers of various fields in automatic data analysis and indexing. For image database application, one finds images with the same image content but perturbed by zooming, scaling and rotation etc. For the pu...
| Main Authors: | , |
|---|---|
| Other Authors: | |
| Format: | Others |
| Language: | zh-TW |
| Published: |
2004
|
| Online Access: | http://ndltd.ncl.edu.tw/handle/45212417155929685979 |
| Summary: | 碩士 === 義守大學 === 資訊工程學系 === 92 === Content-based image retrieval (CBIR) has attracted many researchers of various fields in automatic data analysis and indexing. For image database application, one finds images with the same image content but perturbed by zooming, scaling and rotation etc. For the purpose of image recognition in such databases we employ features based on statistics stemming from fractal transforms of gray-scale images.
Fractal Image Compression provides high compression ratio and high-restored image qualities. In this paper we propose a novel method for CBIR using Fractal features. We show how the features derived from these statistical aspects can be made invariant to zooming or other perturbation. With a defined invariance measurement, we provide numerical results for CBIR application.
|
|---|