Abstract
Nowadays, every document is very essential to be digitized. Increase in the gadgets where everyone likes to take the information in the form of images, but these images contains important information and necessary to be digitize. To do the digitization text detection in an image is one of the important stage in any field of document image analysis. But its not an easy task due to some of the challenges like complex background, varying light condition, low resolution etc. Hence, this work proposed detection of text in images. The proposed methodology consists of three steps. Initially the gabor filter is applied to extract the uncertainty features of the images. Then, 2D wavelet transform is applied to decompose the text information. Finally non-text information is removed using textual features based on the edge information. The proposed method is tested on MRRC and MSRA-TD500 standard dataset and obtained encouraging results.
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Naveena, C., Ajay, B.N., Manjunath Aradhya, V.N. (2019). Transform-Based Text Detection Approach in Images. In: Satapathy, S., Bhateja, V., Somanah, R., Yang, XS., Senkerik, R. (eds) Information Systems Design and Intelligent Applications. Advances in Intelligent Systems and Computing, vol 863. Springer, Singapore. https://doi.org/10.1007/978-981-13-3338-5_40
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DOI: https://doi.org/10.1007/978-981-13-3338-5_40
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