Review of Optical Character Recognition using Pytesseract

In recent years the research done in the field of ocr is advanced to the next level of understanding irrespective of machines and computers. The development of digital libraries throughout the world has led to the conversion of all photographic images into an edited format which is easy to understand and in the upcoming centuries irrespective of Handwriting Styles. The Ocr converts the document with the help of ANN and AI to increase the training of the system to improve its accuracy rate. The ocr faces a complex problem because of different writing pattern and different character for different type of languages various recognition techniques like Character Normalization, Correlation, Neural Network, Recognition, Hidden Markov Model, and Correlation method. In our research paper we explain the different types of ocr that are available in the market and the customer can use it on his basic requirement need. This research paper deals with the new technique that is applicable for creating an improved Ocr which results in improved accuracy.