Abstract
Detecting and recognizing text in natural scene images and videos is vital for several real-world applications, such as in the analysis of Crime scene CCTV footage, sports videos, and autonomous driving, to name a few. Therefore, one can expect several challenges, namely arbitrarily oriented and shaped text detection and identification in movies and natural environments. Many methods have been developed in the past to address these challenges, including advanced deep-learning models and transformers. Due to several methods available in the literature, it is not so easy to understand the open challenges, applications, directions, scope, limitations, and weaknesses of the methods. Therefore, there is a need to write a survey/review to highlight and discuss the strengths and weaknesses of the developed methods. This survey/review presents different categories of work and discusses their importance, limitations, new challenges, applications, and, finally, directions such that readers can choose appropriate methods and directions to carry out research work in the field of text detection/recognition in the natural scene and videos.
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