TY  - JOUR
T1  - Automatic Image Annotation Using Binary Decision SVM-AN Integration Framework
AU - , G. Suresh Kumar AU - , R. Baskaran AU - , A. Kannan 
JO  - Asian Journal of Information Technology
VL  - 5
IS  - 4
SP  - 408
EP  - 412
PY  - 2006
DA  - 2001/08/19
SN  - 1682-3915
DO  - ajit.2006.408.412
UR  - https://makhillpublications.co/view-article.php?doi=ajit.2006.408.412
KW  - Image features
KW  -color
KW  -shape
KW  -annotataion
KW  -support vector machines
AB  - Automatic image annotation is a process of assigning semantic keywords to images and these
annotations are used to retrieve the unlabeled images from large image collections by using semantic query
texts. We are proposing the AIAS (Automatic Image Annotation System), which provides a effective
mechanism for Annotating images using an active learning framework. The visual features like color and shape
gives a great evidence for representing image blobs and its usage for image annotation has been explored in
this study. The extracted image feature vectors (color, shape) and training keywords are used by machine
learning techniques to automatically apply annotations to new images. During training phase the SVM (Support
Vector machine) generation process learns the correlations between image features and training keywords. The
trained model provides the mapping between training image data set and semantic keywords and then the
trained decision model can be used for the automatic image annotation process.
ER  -