PhD Seminar: Multiscale Detection of Circles, Ellipses and Line Segments, Robust to Noise and Blur

Title: Multiscale Detection of Circles, Ellipses and Line Segments, Robust to Noise and Blur

Author: Onofre Martorell Nadal

Abstract: This paper proposes  a basic taxonomy of image contours.  We aim at classifying  smooth curves into five categories, namely, circles, ellipses, line segments, arcs of circles {and arcs of ellipses}. These geometrical structures have been chosen as they serve as input of many computer vision tasks. The proposed strategy is applied on a set of initial disjoint contours, which are  grouped together to form the aforementioned structures. These, in turn, are validated using an a contrario approach that guarantees a reduced number of false detections. The use of a multiscale strategy permits the detection at different resolution levels,  which makes the method robust to noise and blur.

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