An Efficient Automatic Redeye Detection and Correction Algorithm

Authors:
Huitao Luo;Jonathan Yen;Dan Tretter
Affiliations:
Hewlett-Packard Labs, Palo Alto, CA;Hewlett-Packard Labs, Palo Alto, CA;Hewlett-Packard Labs, Palo Alto, CA
Venue:
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 2 - Volume 02
Year:
2004

Citing 0
Cited 3

Red Eye Detection through Bag-of-Keypoints Classification

ICIAP '09 Proceedings of the 15th International Conference on Image Analysis and Processing
Red-eyes removal through cluster-based boosting on gray codes

Journal on Image and Video Processing - Special issue on emerging methods for color image and video quality enhancement
Automatic redeye removal for smart enhancement of photos of unknown origin

VISUAL'05 Proceedings of the 8th international conference on Visual Information and Information Systems

Quantified Score

Hi-index	0.00

Visualization

Abstract

A fully automatic redeye detection and correction algorithm is presented to address the redeye artifacts in digital photos. The algorithm contains a redeye detection part and a correction part. The detection part is modeled as a feature based object detection problem. Adaboost is used to simultaneously select features and train the classifier. A new feature set is designed to address the orientation-dependency problem associated with the Haar-like features commonly used for object detection design. For each detected redeye, a correction algorithm is applied to do adaptive desaturation and darkening over the redeye region.