A trainable retrieval system for cartoon character images

This paper proposes a novel method to retrieve cartoon character images in a database or network. In this method, partial features of an image, defined as regions and aspects, are used as keys to identify cartoon character images. The similarities between a query cartoon character image and the images in the database are computed by using these features. Based on the similarities, the cartoon images same or similar to the query image are identified and retrieved from the database. Moreover, our method adopts a training scheme to reflect the user´s subjectivity. The training emphasizes the significant regions or aspects by assigning more weight based on the user´s preferences and actions, such as selecting a desired image or an area of an image. These processes make the retrieval more effective and accurate. Experimental results verify the effectiveness and retrieval accuracy of the method.