Automatic Extraction of Object Region from Photographs
This paper presents a new method for automatically extracting an object region from a photograph based upon a well-known method “Intelligent Scissors” (IS). For our application, it will be shown that (1) the cost should not be based on accumulated cost adopted by IS but rather on average cost and (2) only a few past pixels are needed for deciding the future route. It will be shown that our new method will be able to extract object region with a correct rate of approximately 93% if object images are well-focused.
- 1.Takeshi Saitoh and Toyohisa Kaneko. Automatic recognition of wild flowers. IEICE (Japan), J84-D-II(7):1419–1429, Jul. 2001.Google Scholar
- 3.Eric N. Mortensen and William A. Barrett. Intelligent scissors for image composition. Computer Graphics, SIGGRAPH 95 Conference Proceedings, pages 191–198, August 1995.Google Scholar
- 4.Detlev Stalling and Hans-Chrisitian Hege. Intelligent scissors for medical image segmentation. Proc. of 4th Freiburger Workshop Digitale Bildverarbeitung in der Medizin, pages 32–36, 1996.Google Scholar
- 5.Mark A. Ruzon and Carlo Tomasi. Alpha estimation in natural images. IEEE Conf. on Computer Vision and Pattern Recognition 2000, pages 18–25, 2000.Google Scholar
- 10.Tomoo Mitsunaga, Taku Yokoyama, and Takashi Totsuka. Autokey: Human assisted key extraction. Computer Graphics, SIGGRAPH 95 Conference Proceedings, pages 265–272, August 1995.Google Scholar