PROCEEDINGS ARTICLE | January 19, 2010
Proc. SPIE. 7537, Digital Photography VI
KEYWORDS: Eye, Facial recognition systems, Statistical analysis, Detection and tracking algorithms, Image processing, Hough transforms, Image analysis, Shape analysis, Signal detection, Binary data
The high level context image analysis regards many fields as face recognition, smile detection, automatic red eye removal,
iris recognition, fingerprint verification, etc. Techniques involved in these fields need to be supported by more powerful
and accurate routines. The aim of the proposed algorithm is to detect elliptical shapes from digital input images. It can
be successfully applied in topics as signal detection or red eye removal, where the elliptical shape degree assessment can
improve performances. The method has been designed to handle low resolution and partial occlusions. The algorithm is
based on the signature contour analysis and exploits some geometrical properties of elliptical points. The proposed method
is structured in two parts: firstly, the best ellipse which approximates the object shape is estimated; then, through the
analysis and the comparison between the reference ellipse signature and the object signature, the algorithm establishes if
the object is elliptical or not. The first part is based on symmetrical properties of the points belonging to the ellipse, while
the second part is based on the signature operator which is a functional representation of a contour. A set of real images
has been tested and results point out the effectiveness of the algorithm in terms of accuracy and in terms of execution time.
