AI*IA '09: Proceedings of the XIth International Conference of the Italian Association for Artificial Intelligence Reggio Emilia on Emergent Perspectives in Artificial Intelligence
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Image segmentation is an essential topic in a document processing system, and also is an important initial task for higher level image processing such as recognition or object tracking since recent years. In this paper we propose a method for segmentation and extraction of the regions of mathematical formulae and graphics in an academic paper. First, an academic paper image is transformed into a binary image by Ohtsu's method. Second, the boundary blank spaces of the binary image are removed and then the image is recursively segmented and extracted by vertical and horizontal projection profiles. We apply the proposed method to 150 academic paper images, and show that the method is adaptable, robust and effective for segmentation.