Image retrieval using augmented block truncation coding techniques
Proceedings of the International Conference on Advances in Computing, Communication and Control
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Content-based image retrieval by specifying composition of images has been studied. Compositional parameters are extracted from images by image segmentation and object extraction procedures. Query is specified through an interactive procedure controlled by a genetic algorithm: First, a user selects one of seven composition templates, each of which represents the typical composition. The system then successively generates patterns of 驴composition models驴 according to the templates selected. These composition models describe the pattern of object distribution within an image. A user iteratively selects composition models, which properly describe the composition he/she wants. Because of this interactive and iterative process, the system obtains parameter values for an evaluation function. The function is used for judging conformity of images to the query. This method reduces the user's burden of properly specifying the query corresponding to the composition and reflecting user's preference. Experiments proved the effectiveness of the method.