In this paper, we present a recommendation system for the automatic design of magazine covers. Our users are nondesigner designers: individuals or small and medium businesses who want to design without hiring a professional designer while still wanting to create aesthetically compelling designs. Because a design should have a purpose, we suggest a number of semantic features to the user, e.g., "clean and clear," "dynamic and active," or "formal," to describe the color mood for the purpose of his/her design. Based on these high level features and a number of low level features, such as the complexity of the visual balance in a photo, our system selects the best photos from the user's album for his/her design. Our system then generates several alternative designs that can be rated by the user. Consequently, our system generates future designs based on the user's style. In this fashion, our system personalizes the designs of a user based on his/her preferences.

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In this paper, we present a JPEC-compliant method for the efficient compression of compound documents using variable quantization. Based on the DCT activity of each 8 x 8 block, our scheme automatically adjusts the quantization scaling factors so that test blocks are compressed at higher quality than image blocks. Results from three different quantization mappings are also reported.

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