Abstract
A novel method for 2D shape recognition is proposed. The method employs as a dissimilarity measure the degree of morphing between a test shape and a reference shape. A physics-based approach substantiates the degree of morphing as a deformation energy and casts the problem as an energy minimization problem. The method operates upon key segmentation points that are provided by an appropriate segmentation algorithm. The recognition paradigm is invariant to translation, rotation, and scaling. It can handle both convex and non-convex shapes. The proposed system exhibits robust recognition behavior and real-time performance in a series of experiments. The experiments also highlight the ability of the method to recognize deformable shapes.
Original language | English (US) |
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Pages (from-to) | 1651-1656 |
Number of pages | 6 |
Journal | Proceedings - IEEE International Conference on Robotics and Automation |
Volume | 2 |
State | Published - 1997 |
Event | Proceedings of the 1997 IEEE International Conference on Robotics and Automation, ICRA. Part 3 (of 4) - Albuquerque, NM, USA Duration: Apr 20 1997 → Apr 25 1997 |