Thomas, A.O.[Achint Oommen],
Rusu, A.[Amalia],
Govindaraju, V.[Venu],
Synthetic handwritten CAPTCHAs,
PR(42), No. 12, December 2009, pp. 3365-3373.
Elsevier DOI
0909
HIP; CAPTCHA; Handwriting generation
BibRef
Rusu, A.[Amalia],
Thomas, A.O.[Achint Oommen],
Govindaraju, V.[Venu],
Generation and use of handwritten CAPTCHAs,
IJDAR(13), No. 1, March 2010, pp. xx-yy.
Springer DOI
1003
BibRef
Ramaiah, C.[Chetan],
Plamondon, R.[Rejean],
Govindaraju, V.[Venu],
A sigma-lognormal model for character level CAPTCHA generation,
ICDAR15(966-970)
IEEE DOI
1511
BibRef
Earlier:
A Sigma-Lognormal Model for Handwritten Text CAPTCHA Generation,
ICPR14(250-255)
IEEE DOI
1412
Accuracy
BibRef
Starostenko, O.[Oleg],
Cruz-Perez, C.[Claudia],
Uceda-Ponga, F.[Fernando],
Alarcon-Aquino, V.[Vicente],
Breaking text-based CAPTCHAs with variable word and character
orientation,
PR(48), No. 4, 2015, pp. 1101-1112.
Elsevier DOI
1502
Breaking CAPTCHA
BibRef
Cruz-Perez, C.[Claudia],
Starostenko, O.[Oleg],
Uceda-Ponga, F.[Fernando],
Alarcon-Aquino, V.[Vicente],
Reyes-Cabrera, L.[Leobardo],
Breaking reCAPTCHAs with Unpredictable Collapse: Heuristic Character
Segmentation and Recognition,
MCPR12(155-165).
Springer DOI
1208
CAPTCHA.
BibRef
Khan, M.[Majid],
Shah, T.[Tariq],
Batool, S.I.[Syeda Iram],
A new implementation of chaotic S-boxes in CAPTCHA,
SIViP(10), No. 1, February 2016, pp. 293-300.
WWW Link.
1601
BibRef
Hajjdiab, H.[Hassan],
Random Image Matching CAPTCHA System,
ELCVIA(16), No. 3, 2017, pp. 1-13.
DOI Link
1801
BibRef
Kwon, H.[Hyun],
Kim, Y.[Yongchul],
Yoon, H.[Hyunsoo],
Choi, D.[Daeseon],
CAPTCHA Image Generation Systems Using Generative Adversarial Networks,
IEICE(E101-D), No. 2, February 2018, pp. 543-546.
WWW Link.
1802
BibRef
Chen, Z.[Zhe],
Ma, W.F.[Wei-Feng],
Xu, N.F.[Nan-Fan],
Ji, C.T.[Cao-Ting],
Zhang, Y.L.[Yu-Lai],
SiameseCCR: a novel method for one-shot and few-shot Chinese CAPTCHA
recognition using deep Siamese network,
IET-IPR(14), No. 12, October 2020, pp. 2855-2859.
DOI Link
2010
BibRef
Zhang, J.M.[Jia-Ming],
Sang, J.[Jitao],
Xu, K.Y.[Kai-Yuan],
Wu, S.X.[Shang-Xi],
Zhao, X.[Xian],
Sun, Y.F.[Yan-Feng],
Hu, Y.L.[Yong-Li],
Yu, J.[Jian],
Robust CAPTCHAs Towards Malicious OCR,
MultMed(23), 2021, pp. 2575-2587.
IEEE DOI
2109
CAPTCHAs, Optical character recognition software, Robustness,
Distortion, Character recognition, Machine learning, OCR
BibRef
Hitaj, D.[Dorjan],
Hitaj, B.[Briland],
Jajodia, S.[Sushil],
Mancini, L.V.[Luigi V.],
Capture the Bot: Using Adversarial Examples to Improve CAPTCHA
Robustness to Bot Attacks,
IEEE_Int_Sys(36), No. 5, September 2021, pp. 104-112.
IEEE DOI
2110
CAPTCHAs, Perturbation methods, Task analysis, Machine learning,
Security, Neural networks, Encoding, Security and Privacy, CAPTCHA,
Adversarial Examples
BibRef
Acien, A.[Alejandro],
Morales, A.[Aythami],
Fierrez, J.[Julian],
Vera-Rodriguez, R.[Ruben],
BeCAPTCHA-Mouse: Synthetic mouse trajectories and improved bot
detection,
PR(127), 2022, pp. 108643.
Elsevier DOI
2205
CAPTCHA, Bot detection, Behavior, Biometrics, Mouse, Neuromotor
BibRef
Shi, C.H.[Cheng-Hui],
Xu, X.G.[Xiao-Gang],
Ji, S.L.[Shou-Ling],
Bu, K.[Kai],
Chen, J.H.[Jian-Hai],
Beyah, R.[Raheem],
Wang, T.[Ting],
Adversarial CAPTCHAs,
Cyber(52), No. 7, July 2022, pp. 6095-6108.
IEEE DOI
2207
CAPTCHAs, Security, Usability, Image synthesis, Computers, Resilience,
Adversarial image, usable security
BibRef
Arora, A.[Akanksha],
Garg, H.[Hitendra],
Shivani, S.[Shivendra],
Anti-phishing technique based on dynamic image captcha using multi
secret sharing scheme,
JVCIR(88), 2022, pp. 103624.
Elsevier DOI
2210
Phishing, Dynamic image CPTCHA, Visual cryptography, Multi secret sharing
BibRef
Wang, P.[Ping],
Gao, H.[Haichang],
Guo, X.Y.[Xiao-Yan],
Xiao, C.X.[Chen-Xuan],
Qi, F.Q.[Fu-Qi],
Yan, Z.[Zheng],
An Experimental Investigation of Text-Based CAPTCHA Attacks and Their
Robustness,
Surveys(55), No. 9, January 2023, pp. xx-yy.
DOI Link
2302
deep learning, robustness study, Text-based CAPTCHA, attack
BibRef
Ferreira, D.D.[Diogo Daniel],
Leira, L.[Luís],
Mihaylova, P.[Petya],
Georgieva, P.[Petia],
Breaking Text-Based CAPTCHA with Sparse Convolutional Neural Networks,
IbPRIA19(II:404-415).
Springer DOI
1910
BibRef
Jalwana, M.A.A.K.[M.A. Asim K.],
Khan, M.M.[Muhammad Murtaza],
Ilyas, M.U.[Muhammad U.],
Automatic Identification of CAPTCHA Schemes,
ISVC14(II: 416-426).
Springer DOI
1501
BibRef
Thomas, A.O.[Achint O.],
Choudhury, S.[Sulabh],
Govindaraju, V.[Venu],
Leveraging the Mixed-Text Segmentation Problem to Design Secure
Handwritten CAPTCHAs,
FHR10(13-18).
IEEE DOI
1011
BibRef
Zhang, T.[Tao],
Li, W.X.[Wen-Xiang],
Zhang, Y.[Yan],
Ping, X.J.[Xi-Jian],
Detection of LSB matching steganography based on the Laplacian model of
pixel difference distributions,
ICIP10(221-224).
IEEE DOI
1009
BibRef
Earlier:
Detection of LSB matching steganography based on distribution of pixel
differences in natural images,
IASP10(548-552).
IEEE DOI
1004
BibRef
Baird, H.S.,
Moll, M.A.,
Wang, S.Y.[Sui-Yu],
ScatterType: a legible but hard-to-segment CAPTCHA,
ICDAR05(II: 935-939).
IEEE DOI
0508
CAPTCHA.
BibRef
Wang, S.Y.[Sui-Yu],
Bentley, J.L.[Jon L.],
CAPTCHA Challenge Tradeoffs: Familiarity of Strings versus Degradation
of Images,
ICPR06(III: 164-167).
IEEE DOI
0609
CAPTCHA.
BibRef
Moy, G.,
Jones, N.,
Harkless, C.,
Potter, R.,
Distortion estimation techniques in solving visual CAPTCHAs,
CVPR04(II: 23-28).
IEEE DOI
0408
Completely Automated Public Turing Test to Tell Computers and Humans
Apart. (embed words in noise to make sure a person is there.)
BibRef
Mori, G.,
Malik, J.,
Recognizing Objects in Adversarial Clutter: Breaking a Visual CAPTCHA,
CVPR03(I: 134-141).
IEEE DOI
0307
BibRef
Chapter on OCR, Document Analysis and Character Recognition Systems continues in
Font Recognition, Multiple Fonts, Script Type, etc. .