Automatic image search based on improved feature descriptors and decision tree
Integrated Computer-Aided Engineering
A review on automatic image annotation techniques
Pattern Recognition
Semantic analysis of 3d anatomical medical images for sub-image retrieval
MCBR-CDS'11 Proceedings of the Second MICCAI international conference on Medical Content-Based Retrieval for Clinical Decision Support
An annotation rule extraction algorithm for image retrieval
Pattern Recognition Letters
Reordering video shots for event classification using bag-of-words models and string kernels
Proceedings of the 27th Conference on Image and Vision Computing New Zealand
Structural image retrieval using automatic image annotation and region based inverted file
Journal of Visual Communication and Image Representation
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Image data is as common as textual data in this digital world. There is an urgent demand of image management tools as efficient as those text search engines. Decades of research on image retrieval has found there is a significant gap between the existing content based image retrieval and semantic interpretation of images by human. As a result, recent research on image retrieval has shifted to semantic image retrieval. Many semantic image retrieval models have been proposed, however, these methods are still alienated from the widely accepted text based retrieval method. In this paper, we propose to unite the semantic image retrieval model with text based retrieval using a novel region based inverted file indexing method. For this purpose, images are translated into textual documents which are then indexed and retrieved the same way as the conventional text based search. Results show that our method not only provides text based search efficiency, but also better performance than the conventional low level image retrieval.