  Character segmentation has long been one of the most critical areas of
optical character recognition process. Through this operation, an image of a
sequence of characters, which may be connected in some cases, is decomposed
into sub-images of individual alphabetic symbols. In this paper, segmentation
of cursive handwritten script of world's fourth popular language, Bengali, is
considered. Unlike English script, Bengali handwritten characters and its
components often encircle the main character, making the conventional
segmentation methodologies inapplicable. Experimental results, using the
proposed segmentation technique, on sample cursive handwritten data containing
218 ideal segmentation points show a success rate of 97.7%. Further
feature-analysis on these segments may lead to actual recognition of
handwritten cursive Bengali script.
