Optical Character Detection and Recognition for Image-Based in Natural Scene

Abstract

In recent years, Optical Character Recognition(OCR) is widely used in machine vision. In this paper, we investigated the problem of optical character detection and recognition for Image-based in natural scene. The Optical Character Recognition is divided into three steps: (1) Selecting the candidate regions through image preprocessing. (2) The detection neural network is used to classify each region. The purpose is to retain text regions and remove non-text regions. (3) The recognition neural network is used to identify the characters in the text regions. We propose a novel algorithm. It integrates image preprocessing with Maximally Stable Extremal Regions(MSER), the neural network architecture of detection and the neural network architecture of recognition. Compared with previous works, the proposed algorithm has three distinctive properties: (1) We propose a new process of OCR algorithm. (2) The application scene of OCR algorithm is the images of natural scene. (3) The training data of recognition does not need artificial labels and can be generated indefinitely. Moreover, the algorithm has achieved good results in detection and recognition.