Character (mathematics)

Chromatography

Handwriting recognition

Set (abstract data type)

Computer science

Time delay neural network

Neocognitron

Optical character recognition

Segmentation

Character recognition

Pattern recognition (psychology)

Mathematics

Image (mathematics)

Data set

Document processing

Intelligent character recognition

Artificial intelligence

Geometry

Chemistry

Programming language

Sample (material)

Intelligent word recognition

Artificial neural network

Feature extraction

Convolutional neural network

Speech recognition

Computers, materials & continua/Computers, materials & continua (Print)

This paper presents a handwritten document recognition system based on the convolutional neural network technique. In today’s world, handwritten document recognition is rapidly attaining the attention of researchers due to its promising behavior as assisting technology for visually impaired users. This technology is also helpful for the automatic data entry system. In the proposed system prepared a dataset of English language handwritten character images. The proposed system has been trained for the large set of sample data and tested on the sample images of user-defined handwritten documents. In this research, multiple experiments get very worthy recognition results. The proposed system will first perform image pre-processing stages to prepare data for training using a convolutional neural network. After this processing, the input document is segmented using line, word and character segmentation. The proposed system get the accuracy during the character segmentation up to 86%. Then these segmented characters are sent to a convolutional neural network for their recognition. The recognition and segmentation technique proposed in this paper is providing the most acceptable accurate results on a given dataset. The proposed work approaches to the accuracy of the result during convolutional neural network training up to 93%, and for validation that accuracy slightly decreases with 90.42%.

Convolutional Neural Network Based Intelligent Handwritten Document Recognition