Web Application System of Handwritten Text Recognition

The problem of text recognition is becoming increasingly important due to the active introduction of digital computing and the widespread use of word processors. Pattern recognition is one of the most difficult from a mathematical point of view and one of the most popular areas of artificial intelligence programming. In the work is researched approaches and methods of solving text recognition problem, improved the performance of the available algorithms for text recognition and created algorithmic software. According to the analysis, neural networks were selected for handwriting recognition. The main advantage of using neural networks is a good generalization ability, the ability to use context analysis and recognize a symbol based on the surrounding symbols. The software implementation features of Hopfield and convolutional neural network, genetic algorithm, which were chosen as effective methods for recognizing handwritten text, were considered. Algorithmic software and web application that uses these methods for the task of handwritten text recognition is developed.