Abstract Image Generation Based on Local Similarity Pattern
Yasufumi Takama and Keisuke Shigemori
Tokyo Metropolitan University, 6-6 Asahigaoka, Hino, Tokyo 191-0065, Japan
The method for generating abstract images from a set of images is proposed. The method selects a representative image from a given set of images, in which the common features in terms of the composition are highlighted with image processing techniques. Common features are extracted based on Local Similarity Pattern (LSP), which has been originally proposed for image retrieval. The selection of representative images is performed based on the difference between the color histogram calculated from a set of regions, of which color features are common, and that calculated from the remaining regions. The experimental results show the performance of the proposed method, in terms of its effectiveness for image classification, as well as the accuracy of selecting representative images. The concept of abstract images is expected to be useful for developing a directory service for searching images on the Web.
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