A signature analysis based method for elliptical shape
Ivana Guarneri, Mirko Guarnera, Giuseppe Messina, Valeria Tomaselli · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2009
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.