Authors:
Chun-Hsien Chou
1
;
Kuo-Cheng Liu
2
and
Shao-Wei Su
1
Affiliations:
1
Tatung University, Taiwan
;
2
Tatung University; Foreign Language and Information Educating Center, Taiwan Hospitality and Tourism College, Taiwan
Keyword(s):
Red-eye, Digital photography, Digital cameras, Uniform color space, Color difference.
Related
Ontology
Subjects/Areas/Topics:
Applications and Services
;
Artificial Intelligence
;
Biomedical Engineering
;
Biomedical Signal Processing
;
Computer Vision, Visualization and Computer Graphics
;
Data Manipulation
;
Health Engineering and Technology Applications
;
Human-Computer Interaction
;
Medical Image Detection, Acquisition, Analysis and Processing
;
Methodologies and Methods
;
Neurocomputing
;
Neurotechnology, Electronics and Informatics
;
Pattern Recognition
;
Physiological Computing Systems
;
Sensor Networks
;
Soft Computing
Abstract:
Red-eye is a highly objectionable defect that often occurs in digital images taken with a flash by modern small cameras. Although many red-eye reduction algorithms were proposed and equipped in most of the digital cameras, none of these algorithms is effective enough. In this paper, an algorithm for automatic detection and correction of red-eyes is proposed. The color detector based on uniform color metric is developed to locate regions of major colors including red-eye color and skin tone. The structure of major colors is adopted to locate candidate red-eye regions. The geometric relationship between the dimension of the human pupil and binocular distance is employed to eliminate most false positives (image regions that look like red-eyes but are not). More than one pairs of red-eyes snapped in different view angles are detected by the proposed algorithm. Detected red-eyes are then corrected by modifying chroma, hue angles and luminance of the associated pixels such that red color i
s removed while maintaining a natural look of the eye. Simulation results show that the proposed algorithm is pretty robust and effective.
(More)