• Journal of Internet Computing and Services
    ISSN 2287 - 1136 (Online) / ISSN 1598 - 0170 (Print)
    https://jics.or.kr/
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A Study on the Characteristics of a series of Autoencoder for Recognizing Numbers used in CAPTCHA


Jae-seung Jeon, Jong-sub Moon, Journal of Internet Computing and Services, Vol. 18, No. 6, pp. 25-34, Dec. 2017
10.7472/jksii.2017.18.6.25, Full Text:  HTML
Keywords: CAPTCHA, Autoencoder, Stacked autoencoder, Denoising, SOFTMAX

Abstract

Autoencoder is a type of deep learning method where input layer and output layer are the same, and effectively extracts and restores characteristics of input vector using constraints of hidden layer. In this paper, we propose methods of Autoencoders to remove a natural background image which is a noise to the CAPTCHA and recover only a numerical images by applying various autoencoder models to a region where one number of CAPTCHA images and a natural background are mixed. The suitability of the reconstructed image is verified by using the softmax function with the output of the autoencoder as an input. And also, we compared the proposed methods with the other method and showed that our methods are superior than others.


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Cite this article
[APA Style]
Jeon, J. & Moon, J. (2017). A Study on the Characteristics of a series of Autoencoder for Recognizing Numbers used in CAPTCHA. Journal of Internet Computing and Services, 18(6), 25-34. DOI: 10.7472/jksii.2017.18.6.25.

[IEEE Style]
J. Jeon and J. Moon, "A Study on the Characteristics of a series of Autoencoder for Recognizing Numbers used in CAPTCHA," Journal of Internet Computing and Services, vol. 18, no. 6, pp. 25-34, 2017. DOI: 10.7472/jksii.2017.18.6.25.

[ACM Style]
Jae-seung Jeon and Jong-sub Moon. 2017. A Study on the Characteristics of a series of Autoencoder for Recognizing Numbers used in CAPTCHA. Journal of Internet Computing and Services, 18, 6, (2017), 25-34. DOI: 10.7472/jksii.2017.18.6.25.