Title :
An object based image retrieval framework based on automatic image annotation
Author :
Bhargava, Anurag ; Shekhar, Shashi ; Arya, K.V.
Author_Institution :
GLA Univ., Mathura, India
Abstract :
Automatic image annotation is the process of assigning relevant keywords to the images. It is considered to be potential research area in current scenario. Annotation to an image can be defined as the information which could describe an image by considering three ways i.e. when these images were taken, what are the different objects available in these images and finally the images belongs to whom. For solving the problem of automatic image annotation, many algorithms have been proposed. Efforts are going on to develop more efficient algorithms. In this paper we have proposed an object based image retrieval algorithm for automatic image annotation. The proposed algorithm considers selection of objects with in an image. This object selection helps in dividing the image into different set of groups on the basis of present objects in an image. Thus, we do not need to extract the whole features from the images when a new image comes, rather we extract features from the objects and matches those features against the different groups of images for the feature matching and effective retrieval based on object selection.
Keywords :
feature extraction; image matching; image retrieval; automatic image annotation; feature extraction; feature matching; image division; object selection; object-based image retrieval framework; relevant keyword assignment process; Algorithm design and analysis; Feature extraction; Image retrieval; Mathematical model; Speech; Support vector machines; Training; Image Annotation; Image Retrieval; Image Similarity; Object marking; SURF; SVM;
Conference_Titel :
Industrial and Information Systems (ICIIS), 2014 9th International Conference on
Conference_Location :
Gwalior
Print_ISBN :
978-1-4799-6499-4
DOI :
10.1109/ICIINFS.2014.7036485