A global non-parametric sampling based image matting
- Resource Type
- Conference
- Authors
- Alam, Naveed; Sarim, Muhammad; Shaikh, Abdul Basit
- Source
- 2013 IEEE 9th International Conference on Emerging Technologies (ICET) Emerging Technologies (ICET), 2013 IEEE 9th International Conference on. :1-6 Dec, 2013
- Subject
- Communication, Networking and Broadcast Technologies
Components, Circuits, Devices and Systems
Fields, Waves and Electromagnetics
Power, Energy and Industry Applications
Robotics and Control Systems
Signal Processing and Analysis
Image color analysis
Mathematical model
Optimization
Equations
Estimation
Robustness
Wires
Alpha matte
Non-parametric
Global sampling method
- Language
Image matting is a process of separating the foreground objects from an image along with opacity values for each pixel. It is an under-constraint problem hence a user interaction is required to identify the definite foreground, background and semi-transparent pixels. In general the information in the definite foreground and background regions is modeled locally to estimate the foreground and background color of the pixels in the semi-transparent region which are then used to estimate opacity values. A global non-parametric sampling based approach is presented which incorporates not only the color information in the foreground and background regions but also utilizes the local structure of an image to improve the quality of the estimate matte. This global sampling approach reduces the segmentation mis-classification that is incorporated in the resulting alpha matte by considering only the local color information. The results obtained are comparable to the state of the art image matting techniques on a standard dataset.