OTSU Guided Adaptive Binarization of CAPTCHA Image using Gamma Correction
Shi Cunzhao; Wang Yanna; Xiao Baihua; Wang Chunheng
Conference NameInternational Conference on Pattern Recognition(ICPR)
Source PublicationICPR
Conference Date2016.12.4-2016.12.8
Conference PlaceMexico
AbstractGamma correction, a nonlinear operation, has long
been used to code and decode luminance or tristimulus values
in video or still image systems [1]. In this paper, we make the
following observations: for CAPTCHA images which could not be
well binarized using the threshold of OTSU, there exists a gamma
corrected image which could be well segmented by the OTSU
threshold and the value of the best gamma could be revealed
by observing the maximal inter-class variance (MICV) values
of different images transformed by different values of gamma.
Concretely, we convert the R, G, B channels of the original
CAPTCHA image with different gamma values and transform
the color images to gray-level images. Each gray-level image could
be then segmented by the threshold acquired by OTSU. By linking
each gamma value with the corresponding maximal inter-class
variance value, we could draw a changing curve of variance
values versus gamma. The best gamma could be acquired by
finding the point whose related MICV starts to change slowly.
Moreover, the polarity of the image could also be revealed by the
changing trend of the curve. Experimental results on different
categories of CAPTCHA images demonstrate the effectiveness of
the observations for binarizing the CAPTCHA images and telling
the polarity as well.

KeywordBinarization Gamma Correction Captcha Image
Document Type会议论文
Corresponding AuthorShi Cunzhao
Recommended Citation
GB/T 7714
Shi Cunzhao,Wang Yanna,Xiao Baihua,et al. OTSU Guided Adaptive Binarization of CAPTCHA Image using Gamma Correction[C],2016.
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