Urdu-Text Detection and Recognition in Natural Scene Images Using Deep Learning

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

Computers Materials & Continua ◽

10.32604/cmc.2019.05990 ◽

2019 ◽

Vol 61 (1) ◽

pp. 289-300 ◽

Cited By ~ 12

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

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Text detection and script identification in natural scene images using deep learning

Computers & Electrical Engineering ◽

10.1016/j.compeleceng.2021.107043 ◽

2021 ◽

Vol 91 ◽

pp. 107043

Author(s):

Ashwaq Khalil ◽

Moath Jarrah ◽

Mahmoud Al-Ayyoub ◽

Yaser Jararweh

Keyword(s):

Deep Learning ◽

Text Detection ◽

Natural Scene ◽

Script Identification ◽

Natural Scene Images

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Devanagari Text Detection From Natural Scene Images

International Journal of Computer Vision and Image Processing ◽

10.4018/ijcvip.2020070104 ◽

2020 ◽

Vol 10 (3) ◽

pp. 44-59

Author(s):

Sankirti Sandeep Shiravale ◽

R. Jayadevan ◽

Sanjeev S. Sannakki

Keyword(s):

Edge Detection ◽

Image Understanding ◽

Text Detection ◽

Experimental Results ◽

Combined Approach ◽

Natural Scene ◽

Light Conditions ◽

The Individual ◽

Natural Scene Images ◽

Better Than

Text present in a camera captured scene images is semantically rich and can be used for image understanding. Automatic detection, extraction, and recognition of text are crucial in image understanding applications. Text detection from natural scene images is a tedious task due to complex background, uneven light conditions, multi-coloured and multi-sized font. Two techniques, namely ‘edge detection' and ‘colour-based clustering', are combined in this paper to detect text in scene images. Region properties are used for elimination of falsely generated annotations. A dataset of 1250 images is created and used for experimentation. Experimental results show that the combined approach performs better than the individual approaches.

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