ANALYSIS AND REVIEW OF HANDWRITTEN TEXT RECOGNITION TECHNIQUES IN DEEP LEARNING

Numerous academic and business interests exist in automatic handwritten text recognition.Deep learning approaches now excel in teaching the ability to detect handwritten text.The key issue in computer vision is handwriting recognition, and the biggest obstacle in this discipline is dealing with the great range of handwriting styles used by different writers in various languages.The difficulty of text recognition is made more difficult by the similarities between the nearby characters.It is extremely difficult to precisely describe the handwritten characters due to the wide range of writing styles used by different authors and the complicated properties of those characters.This research offers a thorough analysis of the handwritten recognition approach using different classifier, different feature extraction techniques and different parameters.