A Wavelet-Based Image Indexing, Clustering, and Retrieval Technique Based on Edge Feature
This paper proposes a technique for indexing, clustering and retrieving images based on their edge features. In this technique, images are decomposed into several frequency bands using the Haar wavelet transform. From the one-level decomposition sub-bands an edge image is formed. Next, the higher or...
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Format: | Buchkapitel |
Sprache: | eng |
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Zusammenfassung: | This paper proposes a technique for indexing, clustering and retrieving images based on their edge features. In this technique, images are decomposed into several frequency bands using the Haar wavelet transform. From the one-level decomposition sub-bands an edge image is formed. Next, the higher order auto-correlation function is applied on the edge image to extract the edge features. These higher order autocorrelation features are normalized to generate a compact feature vector, which is invariant to shift, image size and gray level. Then, these feature vectors are clustered by a self-organizing map (SOM) based on their edge feature similarity. The performed experiments show the high precision of this technique in clustering and retrieving images in a large image database environment. |
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ISSN: | 0302-9743 1611-3349 |
DOI: | 10.1007/3-540-45333-4_22 |