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@article{158449,
        author = {A Venkata Srinivasa Rao and V Kavya and Ch N S Manojna and  K Hari Charan and P Nikhil Babu},
        title = {Recognition of Handwritten Telugu documents using HMM},
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {9},
        number = {9},
        pages = {510-514},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=158449},
        abstract = {Indian script recognition is a difficult task. The creation of comprehensive OCR systems for Indian language scripts is still in its early stages. Recently, full OCR systems for Bangla and Devanagari scripts were created. Character touching and overlap are two important issues that Telugu script recognition research should overcome. Telugu character segmentation is a challenging task for character recognition. In this paper, we make an attempt at segmentation and recognition of handwritten Telugu script using the Drop-Fall and HMM models.},
        keywords = {Segmentation, Telugu scripts, Recognition, Drop-Fall model, Hidden Markov model.},
        month = {},
        }