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Background Estimation
Mehdi Ghayoumi, MD Iftakharul Islam, Muslem Al-SaidiDepartment of Computer Science
Kent State University,Kent, OH 44242.
Objective• Fill in the area of an image based on existing background• User selects an area, which is then filled based on surrounding
pixels• Smooth transitions
Introduction
• Object Removal
– Remove object(s) from image
– Fill the hole with information extracted from the surrounding area.
Filled region should look “realistic” to the human eyes
Example
Source Image Target Final Image
Greedy Approach• A Greedy Patch-based Image Inpainting Framework
Diffusion-based Approach
The idea is to track perfectly the local geometry of the damaged
image and allowing diffusion only in the isophotes curves
direction.
Exemplar Based Approach
Idea
1. Sample color values of the surrounding area
2. Generate textures with sampling result to fill the hole
Criminisi’s Algorithm• Assign each pixel with a priority value• Give linear structures higher priorities
Criminisi’s Algorithm
P(p) = C(p)D(p)
Confidence term
Data term
p
Iq pqC
pC
)(
)()(
pp nI
pD
)(
1. Compute the filling priority
Criminisi’s Algorithm
• (a) The confidence term assigns high filling priority to out-pointing appendices (in green) and low priority
to in-pointing ones (in red), thus trying to achieve a smooth and roughly circular target boundary. (b) The
data term gives high priority to pixels on the continuation of image structures (in green) and has the effect
of favoring in-pointing appendices in the direction of incoming structures.
Effects of data and confidence terms
Criminisi’s Algorithm
2. Search for the best matching patch
Criminisi’s Algorithm
In this step, the algorithm fills the region corresponding to Ψp∩Ω by
replicating the corresponding region in the best matching patch Ψ ^q to the
target patch Ψp. Besides, the boundary of the target region δΩ has to be
renewed.
3. Copy the best matching patch information and refresh the
boundary of target region
Criminisi’s Algorithm(cont.)• Structure Propagation by exemplar-based texture synthesis
Criminisi’s Algorithm(cont.)
Improved Criminisi’s Algorithm(cont.)
Expected Results
Input Output
Future Work
• Implementing Algorithms in JAVA• Make and install its Plugin in Imagej
Future Work
• More accurate propagation of curve structures• Solve the problems
References
• A. Criminisi, P. Perez, K. Toyama. Region filling and object removal by exemplar-based Inpainting, IEEE Transactions on Image Processing,2004.
• Christine Guillemot and Olivier Le Meur ,Image Inpainting, Signal Processing Magazin,IEEE,2014.
• Jing Wang and et all, Robust object removal with an exemplar-based image inpainting approach ,Neurocomputing, IEEE,2014.
Thanks!