Abstract
Recognizing text in scene images plays a vital role especially for applications dealing with environmental interactions. For the system to recognize the environment, textual regions present in them hold a great source of information. But the text recognition task in scene images is complicated due to various unavoidable clutter and distortion in the scene images. Font styling in scene images is also not regulated, and hence, there is a lot of touching between fonts as well. Prior to the recognition of text present in the scene image, identification of correct textual regions and extracting textual edges pose as tedious tasks. Inclusion of unwanted edge features in the task will deteriorate the accuracy of the model. In this work, various methodologies which have been proposed for the identification of textual regions, extraction of textual edges, and recognition of text in scenes have been reviewed. Also, a simple implementation of the same has been done using deep learning classifiers.
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Bhavesh Shri Kumar, N., Reddy, D.N.B.K.S., Sairam, K., Naren, J. (2020). Scene Text Recognition: A Preliminary Investigation on Various Techniques and Implementation Using Deep Learning Classifiers. In: Khanna, A., Gupta, D., Bhattacharyya, S., Snasel, V., Platos, J., Hassanien, A. (eds) International Conference on Innovative Computing and Communications. Advances in Intelligent Systems and Computing, vol 1087. Springer, Singapore. https://doi.org/10.1007/978-981-15-1286-5_20
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DOI: https://doi.org/10.1007/978-981-15-1286-5_20
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