Using a group of ellipses to approach the shape contour, a new shape retrieval method is presented in this paper. In order to keep shape-based retrieval invariant to its position, orientation and size, the shape norma...Using a group of ellipses to approach the shape contour, a new shape retrieval method is presented in this paper. In order to keep shape-based retrieval invariant to its position, orientation and size, the shape normalization method is presented. From our research, any closed shape contour can be uniquely decomposed into a group of ellipses, and the original shape contour can be re-constructed using the decomposed ellipses. The ellipse-based shape description and similar retrieval method is introduced in this paper. Based on ellipse's contribution to shape contour, the decomposed ellipses are parted into low-order ellipses and high-order ellipses. The low-order ellipses measure the macroscopic feature of a shape contour, and the high-order ellipses measure the microscopic feature. The two-phase shape matching method is given. Through the experiment test, our method has better shape retrieval effect.展开更多
文摘Using a group of ellipses to approach the shape contour, a new shape retrieval method is presented in this paper. In order to keep shape-based retrieval invariant to its position, orientation and size, the shape normalization method is presented. From our research, any closed shape contour can be uniquely decomposed into a group of ellipses, and the original shape contour can be re-constructed using the decomposed ellipses. The ellipse-based shape description and similar retrieval method is introduced in this paper. Based on ellipse's contribution to shape contour, the decomposed ellipses are parted into low-order ellipses and high-order ellipses. The low-order ellipses measure the macroscopic feature of a shape contour, and the high-order ellipses measure the microscopic feature. The two-phase shape matching method is given. Through the experiment test, our method has better shape retrieval effect.