An Efficient Automatic Redeye Detection and Correction Algorithm

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.

• Type: Conference
• Year: 2004
• Where: ICPR
• Authors: Dan Tretter, Huitao Luo, Jonathan Yen
• Keywords: Automatic Redeye Detection, Computer Vision, ICPR 2004, Redeye Artifacts, Redeye Region