Abstract
Identifying and recognition of breaking news in most of the TV channels in different backgrounds with varying positions from a static image plays a significant role in journalism and multimedia image processing. Now a days it’s very challenging to isolate only breaking news from headlines due to overlapping of many categories of news, keeping all this in mind, a novel methodology is proposed in this paper for detecting specific text as a breaking news from a given multimedia image. Basic digital image processing techniques are used to detect text from the images. The methods like MSER (Maximally Stable Extremal Regions) and SWT (Stroke Width Transform) are used for text detection. The proposed work focuses on extraction of text in breaking news images also discusses the different methods to overcome existing challenges in text detection along with different types of breaking news datasets collected from various news channels are used to identify text from images and comparative study of different text detection methods. The comparative study proves that MSER and SWT is a better technique to detect text in images. Finally using OCR (Optical Character Recognition) technique to extract the breaking news text from the detected regions will help in easy indexing and analysis for journalism and common people. Extensive experiments are carried out to demonstrate the effectiveness of the proposed approach.
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Ridwan, A., Danti, A., Raghavendra, S.P., Aqlan, H.A.A., Arunkumar, N.B. (2019). Breaking News Recognition Using OCR. In: Santosh, K., Hegadi, R. (eds) Recent Trends in Image Processing and Pattern Recognition. RTIP2R 2018. Communications in Computer and Information Science, vol 1037. Springer, Singapore. https://doi.org/10.1007/978-981-13-9187-3_11
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DOI: https://doi.org/10.1007/978-981-13-9187-3_11
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