An Approach for Segmentation Handwritten Kannada Document

ABSTRACT Handwritten text line segmentation is considered to be a major challenge in document image analysis. It has to solve some obstacles that are uncommon in modern printed text. Among the most are: skewed lines, curvilinear lines, touching and overlapping components, usually words or letters, between lines and irregularity in geometrical properties of line. Text line extraction from unconstrained handwritten documents is a challenge because the text lines are often skewed and the space between lines is not obvious. The complexity involved in the segmentation of the Handwritten Documents for Indian languages like Telugu, Tamil and Malayalam. Curved and non-parallel text lines handwritten documents also make the segmentation and recognition challenging. Text line segmentation of handwritten documents written in Kannada script by using Independent Component Analysis (ICA) is taken into consideration