Segmentation And Understanding Of Color Magazine Images

Abstract

An integrated approach to segmentation and understanding of color magazines is proposed. First, a dynamic-cut color quantization method is proposed, which can be used to classify. Next, for block segmentation, a new algorithm is proposed to grow neighboring pixels witj identical colors into blocks more efficiently. After block extraction, several features are used to classify extracted blocks into text blocks and graphic blocks. For construction of blocks from magazine images which usually have complicated background, improved methods for merging text blocks into text areas and graphic blocks into graphic areas are also proposed. These classified areas are then used to analyze the document layout. Methods for finfing titles, abstrcats, section titles, section texts, headers, footers, page numbers, and captions of graphics in magazines are proposed. Experimenta; results are shown to prove the feasibility of the proposed approach.