Abstract
In this paper, the problem of spam filtering for images, a type of fast-spreading spam where the text is included in images to overcome the text-based spam filter. One common method for detecting spam is the optical character recognition system (OCR) that detecting and recognizing the text embedded, following by a classifier which distinguishes spam from ham. Nevertheless, the spammers begin hiding image text for preventing OCR from detecting spam. To recompense for the shortages of the OCR system, a method based on the detection algorithm is proposed for the text region. To estimate the performance of the projected system, the methodology was applied to a group of unwanted images Dredze (available to the public) to check the efficiency of our method which outperforms the initial OCR system in sensible use with a complex background in spam. The test results indicated that the new method gives good text regions detection even for noisy images.
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Dhahi, E.H., Ali, S.A., Naser, M.A. (2020). Text Region Extraction for Noisy Spam Image. In: Mallick, P., Balas, V., Bhoi, A., Chae, GS. (eds) Cognitive Informatics and Soft Computing. Advances in Intelligent Systems and Computing, vol 1040. Springer, Singapore. https://doi.org/10.1007/978-981-15-1451-7_25
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DOI: https://doi.org/10.1007/978-981-15-1451-7_25
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