Publication Type : Conference Proceedings
Publisher : Computational Vision and Bio Inspired Computing, Springer International Publishing
Source : Computational Vision and Bio Inspired Computing, Springer International Publishing, Cham (2018)
ISBN : 9783319717678
Campus : Coimbatore
School : School of Engineering
Department : Computer Science
Year : 2018
Abstract : The Exploration of contextual information is very important for any automatic image annotation system. In this work a method based on kernels and keyword propagation technique is proposed. Automatic annotation with a set of keywords for each image is carried out by learning the image semantics. The similarity between the images is calculated by Hellinger's kernel and Radial Bias Function kernel(RBF)kernel. The images are labelled with multiple keywords using contextual keyword propagation. The results of using the two kernels on the set of features extracted are analysed. The annotation results obtained were validated based on confusion matrix and were found to have a good accuracy. The main advantage of this method is that it can propagate multiple keywords and no definite structure for the annotation keywords has to be considered
Cite this Research Publication : S. L. Nair, Manjusha R., and Dr. Latha Parameswaran, “Kernel Based Approaches for Context Based Image Annotatıon”, Computational Vision and Bio Inspired Computing. Springer International Publishing, Cham, 2018.