• N. Kishore Kumar
• M. Roshan-e-shabha
• R. Pooja Sree
• N. Sushmitha
• D. Rama Krishna

Handwriting recognition has gained a lot of attention in the field of person recognition, voice recognition, pattern recognition and machine learning due to its application in various fields. Optical Character Recognition [OCR] and Handwritten Character Recognition [HCR] has specific domain to apply. Various techniques have been proposed to for person recognition in handwriting recognition system. Hidden Markov Mode[HMM] and Artificial Neural Networks [ANN] based recognition system, is applied to handwriting person recognition with six original features, Delta x, Delta y, writing angle, Delta writing angle, Pen Up / Pen Down bit, and sign(x-max(x)), the baseline system obtained a word error of 13.8%in a 25K-word lexicon, 86-character set, writer-independent task. four new groups of features, a vertical height feature, a space feature, hat strokes feature, and sub stroke features were implemented to improve the characterization of vertical height, inter-word space and other global information. Even though, sufficient studies and papers describes the techniques for converting textual content from a paper document into machine readable form. In coming days person recognition system might serve as a key factor to create a paperless environment by digitizing and proposing existing paper documents. these paper presents a detailed review in the field of handwriting person recognition.

Handwritten Character Recognition, Optical Character Recognition, Hidden Markov Model, Artificial Neural Network.

"HANDWRITING PERSON RECOGNITION USING HIDDEN MARKOV MODEL AND ARTIFICIAL NEURAL NETWORKS", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 3, page no.115-123, March-2019, Available :http://www.jetir.org/papers/JETIR1903J18.pdf

"HANDWRITING PERSON RECOGNITION USING HIDDEN MARKOV MODEL AND ARTIFICIAL NEURAL NETWORKS", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 3, page no. pp115-123, March-2019, Available at : http://www.jetir.org/papers/JETIR1903J18.pdf