A multi-view fusion method for image retrieval
| Autor: | Yuan-ting Yan, Yang-ping Zhang, Shi-bo Zhang |
|---|---|
| Rok vydání: | 2016 |
| Předmět: |
Color histogram
Computer science Color image Color normalization business.industry InformationSystems_INFORMATIONSTORAGEANDRETRIEVAL Feature extraction ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION 020206 networking & telecommunications 02 engineering and technology HSL and HSV Feature (computer vision) Histogram 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Computer vision Visual Word Artificial intelligence business Image retrieval Histogram equalization |
| Zdroj: | CISP-BMEI |
| DOI: | 10.1109/cisp-bmei.2016.7852740 |
| Popis: | Color histogram is an important technique for color image database indexing and retrieving. However, existing color based retrieval techniques are mainly designed for only extracting global or local feature, which cannot provide effective retrieval of images. In this paper, we propose a novel multi-view fusion method for image retrieval by combining the global color with salient regions color feature, which highlights the important characteristics of the salient regions without losing the background information. Firstly, HSV color histogram is quantified rationally as a global descriptor. Secondly, a salient region detection method is introduced to separate the salient regions and the background regions. After that, color histogram of the salient regions is applied to constitute a region-based descriptor. Finally, a CBIR system is designed by using an adaptive weighting method to combine these two descriptors. The relevant retrieval experiments on Corel-1000 show that the proposed approach brings better visual feeling than single feature retrieval, which exceeds at least 9%. |
| Databáze: | OpenAIRE |
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