Segmentation of Frequently Used Handwritten Gujarati Conjunctive Alphabet
Megha N. Parikh, Apurva A. Desai - · 2019
The segmentation of touching symbols is one of the key factors which decrease the performance of the Optical Character Recognition (OCR) system. The existence of touching characters in the documents is a major problem of the effective character segmentation system. In this paper, we have presented an algorithm for the segmentation of frequently used handwritten Gujarati conjunctive characters into its constituent symbols and characters. A predictive algorithm is developed for selecting the possible cut column for the segmentation of conjunctive characters. This algorithm uses the structural properties of the Gujarati alphabet. The possible cut column is defined by using the information derived from the neighboring pixels. This algorithm covers 728 handwritten conjunctive characters of Gujarati Script. In this conjunctive characters are segmented into easily separable characters which can be further sent to the classifier for recognition.