Locating object contours in complex background using improved snakes |
| |
| Affiliation: | 1. Department of Medical Imaging and Radiological Sciences, Kaohsiung Medical University, Kaohsiung, Taiwan;2. Division of Endocrinology and Metabolism, Department of Internal Medicine, Kaohsiung Medical University Hospital, Kaohsiung, Taiwan;3. Department of Medical Imaging, Kaohsiung Medical University Hospital, Kaohsiung, Taiwan;1. Istituto di Bioimmagini e Fisiologia Molecolare - Consiglio Nazionale delle Ricerche (IBFM CNR - LATO), Cefalù, PA, Italy;2. Dipartimento di Biopatologia e Biotecnologie Mediche e Forensi (DIBIMEF), Università degli Studi di Palermo, Palermo, Italy;1. Division of Cardiovascular Diseases, Mayo Clinic, Rochester, MN, USA;2. Division of Biomedical Statistics and Informatics, Mayo Clinic, Rochester, MN, USA;3. Division of Nephrology, Mayo Clinic, Rochester, MN, USA;4. Physiology and Biomedical Engineering, Mayo Clinic, Rochester, MN, USA |
| |
| Abstract: | An active contour model, called snake, can adapt to object boundary in an image. A snake is defined as an energy minimizing spline guided by external constraint forces and influenced by image forces that pull it toward features such as lines or edges. The traditional snake model fails to locate object contours that appear in complex background. In this paper, we present an improved snake model associated with new regional similarity energy and a gravitation force field to attract the snake approaching the object contours efficiently. Experiment results show that our snake model works successfully for convex and concave objects in a variety of complex backgrounds. |
| |
| Keywords: | |
| 本文献已被 ScienceDirect 等数据库收录！ |
|
