Kannada Handwritten document paragraph segmentation is a complex process which involves identification of size, style and pen used for writing. Therefore, it becomes crucial part of converting document into paragraph segmentation. A database of Kannada handwritten document is created and the same has been used for research purposes. In this paper, atmos focus is laid on Kannada handwritten paragraph segmentation with deskewed content. Binarization method of preprocessing technique is used and Run Length Smoothing Algorithm(RLSA) to tackle the problem of segmenting Kannada handwritten documents.