Handwritten Gujarati script recognition with image processing and deep learning

The motive behind writing this paper is to throw light on the proposed application which can be used for detecting and recognizing Gujarati handwritten scripts using image processing and machine learning techniques. It emphasizes the key technologies involved in this process. There is a lot of variation in the handwriting of people and the curves involved in the characters of the Gujarati language and therefore possess a challenge in the process. The paper features all the important phases in character recognition and detection process namely image acquisition, preprocessing, segmentation, classification and recognition, and post-processing. It also emphasizes the key aspects like the designing a neural network suitable for the challenging task of handwritten character recognition in Gujarati scripts, training and testing that model and fine-tuning various hyper-parameters to get the best accuracy. The paper can be referred by researchers and technology enthusiasts to develop systems for Gujarati script recognition. The paper aims to present and deal with special properties associated with Gujarati script.