Boosting gray codes for red eyes removal

S. Battiato, G. M. Farinella, M. Guarnera, G. Messina, D. Ravì

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Citations (Scopus)


Since the large diffusion of digital camera and mobile devices with embedded camera and flashgun, the red-eyes artifacts have de-facto become a critical problem. The technique herein described makes use of three main steps to identify and remove red-eyes. First, red eyes candidates are extracted from the input image by using an image filtering pipeline. A set of classifiers is then learned on gray code features extracted in the clustered patches space, and hence employed to distinguish between eyes and non-eyes patches. Once red-eyes are detected, artifacts are removed through desaturation and brightness reduction. The proposed method has been tested on large dataset of images achieving effective results in terms of hit rates maximization, false positives reduction and quality measure.

Original languageEnglish
Title of host publicationProceedings - 2010 20th International Conference on Pattern Recognition, ICPR 2010
Number of pages4
Publication statusPublished - 2010
Externally publishedYes
Event2010 20th International Conference on Pattern Recognition, ICPR 2010 - Istanbul, Turkey
Duration: 23 Aug 201026 Aug 2010

Publication series

NameProceedings - International Conference on Pattern Recognition
ISSN (Print)1051-4651


Conference2010 20th International Conference on Pattern Recognition, ICPR 2010


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