Document page segmentation using multiscale clustering
The paper details a multiscale clustering technique for document page segmentation. In contrast to existing hierarchical (coarse-to-fine), multi-resolution methods, this image segmentation technique simultaneously uses information from different scaled representations of the original image. The final clustering of image segments is achieved through a fuzzy c-means based similarity measure between vectors in scale space. The segmentation process reduces the effects of insignificant detail and noise. Furthermore, object integrity is preserved in the segmentation process.