Image Recognition System That Uses Visual Word

To deal with a large-scale image database, we design and implement an image recognition system using visual word. First, SIFT (Scale-invariant Feature Transform) features are extracted from the images. Subset of these features is then selected during the feature selection process. Finally selected f...

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Bibliographic Details
Published in2014 International Conference on Information Science & Applications (ICISA) pp. 1 - 2
Main Authors Min-Uk Kim, Kyoungro Yoon
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.05.2014
Subjects
Feature extraction
Image recognition
Indexing
Libraries
Quantization (signal)
Three-dimensional displays
Visualization
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Summary:To deal with a large-scale image database, we design and implement an image recognition system using visual word. First, SIFT (Scale-invariant Feature Transform) features are extracted from the images. Subset of these features is then selected during the feature selection process. Finally selected features are quantized to the visual words. These visual words play an important role at the first search phase and to the overall precision. At the second search, original SIFT features are used to rearrange the result. Experimental results show 93% precision and 2 seconds retrieval time.
ISBN:9781479944439
1479944432
ISSN:2162-9048
DOI:10.1109/ICISA.2014.6847410