DocumentCode :
602032
Title :
A new approach of image inpainting based on PSO algorithm
Author :
Shu-Chiang Chung ; Ta-Wen Kuan ; Chuan-Pin Lu ; Hsin-Yi Lin
Author_Institution :
Dept. of Inf. Technol., Meiho Univ., Pingtung, Taiwan
fYear :
2013
fDate :
12-16 March 2013
Firstpage :
205
Lastpage :
209
Abstract :
In this paper, an efficient approach is developed to incorporate the exemplar-based image of inpainting method and the minimum error boundary of cut technique, that is proposed to improve the image inpainting in a more nature quality with high performance. The approach is based on the particle swarm optimization. Several advantages are addressed as follow. First, the image inpainting in texture with the linear structure is exploited to reasonably inpaint the damaged image in a high priority. Due to set the first priority to inpaint in the linear structure, such a method guarantees the integrality of the linear structure. In addition, the minimum error boundary of cut technique can effectively decrease the unnatural phenomena through inpainting the gap of damaged image. Owing to the damaged one will be dawdling extraordinarily if searching the similar block while inpainting. In this case, the method is proposed by joined the particle swarm optimization algorithm, and the outcome indeed improves the efficiency of image inpainting.
Keywords :
image texture; particle swarm optimisation; PSO algorithm; cut technique; exemplar-based image inpainting method; image inpainting approach; image texture; linear structure; minimum error boundary; particle swarm optimization algorithm; Algorithm design and analysis; Educational institutions; Equations; Mathematical model; PSNR; Particle swarm optimization; Vectors; Exemplar-Based Image Inpainting; Image Inpainting; Minimum Error Boundary Cut; Particle Swarm Optimization;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Orange Technologies (ICOT), 2013 International Conference on
Conference_Location :
Tainan
Print_ISBN :
978-1-4673-5934-4
Type :
conf
DOI :
10.1109/ICOT.2013.6521193
Filename :
6521193
Link To Document :
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