Automatic Image Annotation Using SURF Descriptors

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Automatic Image Annotation Using SURF Descriptors

Show simple item record Sreeraj, M Muhammed Anees, V Santhosh Kumar, G 2014-07-30T05:58:26Z 2014-07-30T05:58:26Z 2012-12-07
dc.description India Conference (INDICON), 2012 Annual IEEE en_US
dc.description.abstract In recent years there is an apparent shift in research from content based image retrieval (CBIR) to automatic image annotation in order to bridge the gap between low level features and high level semantics of images. Automatic Image Annotation (AIA) techniques facilitate extraction of high level semantic concepts from images by machine learning techniques. Many AIA techniques use feature analysis as the first step to identify the objects in the image. However, the high dimensional image features make the performance of the system worse. This paper describes and evaluates an automatic image annotation framework which uses SURF descriptors to select right number of features and right features for annotation. The proposed framework uses a hybrid approach in which k-means clustering is used in the training phase and fuzzy K-NN classification in the annotation phase. The performance of the system is evaluated using standard metrics. en_US
dc.description.sponsorship Cochin University of Science and Technology en_US
dc.language.iso en en_US
dc.publisher IEEE en_US
dc.subject Automatic Image Annotation en_US
dc.subject SURF feature extraction en_US
dc.subject Image classification en_US
dc.subject K-means clustering en_US
dc.subject Fuzzy KNN en_US
dc.title Automatic Image Annotation Using SURF Descriptors en_US
dc.type Article en_US

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