Automated red-eye detection and correction in digital photographs

Author(s):  
Lei Zhang ◽  
Yanftng Sun ◽  
Mingiing Li ◽  
Hongiiang Zhang
2009 ◽  
Vol 55 (3) ◽  
pp. 1006-1014 ◽  
Author(s):  
Seunghwan Yoo ◽  
Rae-Hong Park

2020 ◽  
Vol 17 (4) ◽  
pp. 1692-1695
Author(s):  
K. Sathish ◽  
Kumar Sanu Raj ◽  
J. V. Adithya Chowdary ◽  
Nitish Jahagirdar

Sometimes in Flash Photography red colored patches occurred in human eyes. It is actually a reflection of bright flash light reflected from blood vessels in the eyes, giving the eye an unnatural red hue. Red-eye is a big problem in professional photography. Most red-eye reduction systems in many editing software needed the user to identify the red-eye and make an outline through the red-eye. Here we propose an Automatic Red-Eye Detection System instead. The system contains a red-eye detector that finds bunch of red pixels those are clustered to gather, a state of face detector that used to eliminate most false positives (pixel clusters that look red eyes but are not); and a redeye outline detector. All three detectors are automatically learned from the taken datasets and with a proper classifiers using boosting. For creating a fully Automatic Red-Eye Corrector this system needed to be combined with a functional Red-Eye Reduction model.


Author(s):  
Sebastiano Battiato ◽  
Mirko Guarnera ◽  
Tony Meccio ◽  
Giuseppe Messina
Keyword(s):  

Author(s):  
Vinay Kumar ◽  
Sunil Bhooshan ◽  
Ankita Sood ◽  
Rahul Shahi ◽  
Shashank Mendiratta

Author(s):  
Wonwoo Jang ◽  
Chris sungjin Lee ◽  
Sukchan Kim ◽  
Bongsoon Kang

Author(s):  
Mithun Uliyar ◽  
A.G. Krishna ◽  
P.S.S.B.K Gupta ◽  
J.P Pai

Author(s):  
Leena Lepisto ◽  
Aki Launiainen ◽  
Iivari Kunttu
Keyword(s):  

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