Abstract
The increase in availability of high performance, low-priced, portable digital imaging devices has created an opportunity for supplementing traditional scanning for document image acquisition. Cameras attached to cellular phones, wearable computers, and standalone image or video devices are highly mobile and easy to use; they can capture images making them much more versatile than desktop scanners. Should gain solutions to the analysis of documents captured with such devices become available, there will clearly be a demand in many domains. Images captured from images can suffer from low resolution, perspective distortion, and blur, as well as a complex layout and interaction of the content and background.In this paper, we propose an efficient text detection method based on Maximally Stable Exterme Region (MSER) detector, saying that how to detect regions containing text in an image. It is a common task performed on unstructured scenes, for example when capturing video from a moving vehicle for the purpose of alerting a driver about a road sign . Segmenting out the text from a clutterd scene greatly helps with additional tasks such as optical charater recognition (OCR). The efficiency of any service or product, especially those related to medical field depends upon its applicability. The applicability for any service or products can b achieved by applying thr basic principles of Software Engineering.
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Darshan, H.Y., Gopalkrishna, M.T., Hanumantharaju, M.C. (2015). Text Detection and Recognition Using Camera Based Images. In: Satapathy, S., Biswal, B., Udgata, S., Mandal, J. (eds) Proceedings of the 3rd International Conference on Frontiers of Intelligent Computing: Theory and Applications (FICTA) 2014. Advances in Intelligent Systems and Computing, vol 328. Springer, Cham. https://doi.org/10.1007/978-3-319-12012-6_63
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DOI: https://doi.org/10.1007/978-3-319-12012-6_63
Publisher Name: Springer, Cham
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