Abstract: Page segmentation and classification is the key procedure in document processing. But most current algorithms can only process pages with limited shape of blocks and no skew angle. In this paper, a new approach to page segmentation and classification based on connected components is introduced. First, the connected components in page image are extracted quickly. Then a RLSA algorithm based on the connected components is adopted for page segmentation. Furthermore, distribution of the connected components in one block and global features of the block are analyzed to classify different blocks. This approach not only combines the page segmentation and classification together, which improves the running efficiency, but also takes into consideration the local features of block, which assures the correctness of block classification.