Bangla Handwritten Word Recognition System Using Convolutional Neural Network
Md. Tanvir Hossain, Md. Wahid Hasan, Amit Kumar Das
Abstract
In recent years, Machine Learning and Data Mining based research become prevalent and handwritten recognition is one of the hotcakes. Bangla handwritten word recognition and extraction acquired huge attention in many research sectors like Computer Vision, Image Processing, Machine Learning, and many others for a large field of applications. To tackle this challenging problem, a perfect segmentation and recognition method are described in this paper with a good percentage of accuracy. The main challenge was to introduce a sound segmentation system and merge multi-zoned characters. This paper proposes a multi-zoned character segmentation, and a merging method is also proposed, which can produce the handwritten term. Utilizing Convolutional Neural Network (CNN) for preparing 84% precision is accomplished for character level, and 82% precision is achieved in word level.