scholarly journals Text Detection and Recognition for Natural Scene Images Using Deep Convolutional Neural Networks

2019 ◽  
Vol 61 (1) ◽  
pp. 289-300 ◽  
Author(s):  
Xianyu Wu ◽  
Chao Luo ◽  
Qian Zhang ◽  
Jiliu Zhou ◽  
Hao Yang ◽  
...  
Keyword(s):  
Neural Networks ◽  
Convolutional Neural Networks ◽  
Text Detection ◽  
Natural Scene ◽  
Deep Convolutional Neural Networks ◽  
Natural Scene Images ◽  
Detection And Recognition

End-to-End Analysis for Text Detection and Recognition in Natural Scene Images

2020 ◽  
Author(s):  
Ahlam Alnefaie ◽  
Deepak Gupta ◽  
Monowar H. Bhuyan ◽  
Imran Razzak ◽  
Prashant Gupta ◽  
...  
Keyword(s):  
Text Detection ◽  
Natural Scene ◽  
End To End ◽  
Natural Scene Images ◽  
Detection And Recognition

scholarly journals Improvement of the end-to-end scene text recognition method for “text-to-speech” conversion

2020 ◽  
Vol 18 (06) ◽  
pp. 2050052
Author(s):  
Fazliddin Makhmudov ◽  
Mukhriddin Mukhiddinov ◽  
Akmalbek Abdusalomov ◽  
Kuldoshbay Avazov ◽  
Utkir Khamdamov ◽  
...  
Keyword(s):  
Text Detection ◽  
Text Recognition ◽  
Natural Scenes ◽  
Natural Scene ◽  
Text To Speech ◽  
Convolutional Network ◽  
Full Color ◽  
Active Research ◽  
Natural Scene Images ◽  
Detection And Recognition

Methods for text detection and recognition in images of natural scenes have become an active research topic in computer vision and have obtained encouraging achievements over several benchmarks. In this paper, we introduce a robust yet simple pipeline that produces accurate and fast text detection and recognition for the Uzbek language in natural scene images using a fully convolutional network and the Tesseract OCR engine. First, the text detection step quickly predicts text in random orientations in full-color images with a single fully convolutional neural network, discarding redundant intermediate stages. Then, the text recognition step recognizes the Uzbek language, including both the Latin and Cyrillic alphabets, using a trained Tesseract OCR engine. Finally, the recognized text can be pronounced using the Uzbek language text-to-speech synthesizer. The proposed method was tested on the ICDAR 2013, ICDAR 2015 and MSRA-TD500 datasets, and it showed an advantage in efficiently detecting and recognizing text from natural scene images for assisting the visually impaired.

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