A Survey on Multi Oriented Text Recognition | Original Article

ABSTRACT:

Increasing use of smart phone in our day to day life to capture images initiates a need to recognize text from natural images which is nowadays a hot research topic in the field of computer vision due to its various applications. Text in natural scenes exists in almost every phase of our daily life. From the facade of the buildings in our city to the cover of a book in our library. Undoubtedly, text is among the most brilliant and influential creations of humankind. Despite the enduring research of several decades on optical character recognition (OCR), recognizing texts from natural images is still a difficult task because of series of grand challenges which is still be encountered when detecting and recognizing text. Scene texts are often found in irregular shape (curved, or arbitrarily oriented) and its recognition not yet been well addressed in the literature. Most of the existing methods on text recognition work with regular (horizontal) texts and not generalized to handle irregular texts. This survey is aimed at summarizing and analyzing the major changes and significant progress of multi oriented text recognition in the deep learning era.