A Multimodal Framework for the Recognition of Ancient Tamil Handwritten Characters in Palm Manuscript Using Boolean Bitmap Pattern of Image Zoning

Tamil is one of the oldest languages in the world with rich literature. In the ancient days, the writers, especially in Tamilnadu, used palm leaves to encrypt their writing. A very good example of the usage of Palm leaf manuscripts to store the history is Tamil grammar book named Tolkappiyam which was written during 4th B.C. The ancient literature includes many palm leaf manuscripts that contain Sangam works, classics, Saiva, Vaishnava and Jain works, medical works, food, astronomy & astrology, vaastu & Kaama shastra, jewellery, music, dance & drama, medicine, Siddha and so on. Over the 3, 500 Tamil manuscripts are available in Saraswathi Mahal Library located in Thanjavur, Taminadu, India. In this library, only a few palm leaf manuscripts are digitalized and many are to be digitalized so as to enable quick reference in the future. The objective of the proposed research is to develop the model that can recognize Tamil characters from palm manuscripts and convert them into text format. In the field of handwritten character recognition, image zoning is a widespread technique for feature extraction since it is rightly considered to be able to cope with handwritten pattern variability.