research-article

A Biogeography-Based Optimization Algorithm for Criminisi Algorithm

Authors:

Shi YanAuthors Info & Claims

ICMSSP '19: Proceedings of the 2019 4th International Conference on Multimedia Systems and Signal Processing

Pages 25 - 30

https://doi.org/10.1145/3330393.3330402

Published: 10 May 2019 Publication History

Abstract

The criminisi algorithm is a useful image inpainting approach, but it cost high computational complexity. In order to reduce the computational complexity of image inpainting, an improved Criminisi algorithm is proposed in this paper based on biogeography optimization (BBO). According to the characteristic of Criminisi, the new method uses the migration and mutation of BBO to search the best matching block and overcome the shortcomings of the Criminisi algorithm by searching the best matching block in the unbroken regions in the image. Experimental results show that this algorithm reduces the computational complexity significantly for Criminisi algorithm with maintaining still the good performance.

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Cited By

Srinivasan MChinnadurai MSenthilkumar SDinesh E(2024)An effective video inpainting technique using morphological Haar wavelet transform with krill herd based criminisi algorithmScientific Reports10.1038/s41598-024-66496-x14:1Online publication date: 5-Jul-2024
https://doi.org/10.1038/s41598-024-66496-x

Index Terms

A Biogeography-Based Optimization Algorithm for Criminisi Algorithm
1. Computing methodologies
  1. Computer graphics
    1. Image manipulation
      1. Image processing

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ICMSSP '19: Proceedings of the 2019 4th International Conference on Multimedia Systems and Signal Processing

May 2019

213 pages

ISBN:9781450371711

DOI:10.1145/3330393

Copyright © 2019 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Shenzhen University: Shenzhen University
Sun Yat-Sen University

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Association for Computing Machinery

New York, NY, United States

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Published: 10 May 2019

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ICMSSP 2019

ICMSSP 2019: 2019 4th International Conference on Multimedia Systems and Signal Processing

May 10 - 12, 2019

Guangzhou, China

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Cited By

Srinivasan MChinnadurai MSenthilkumar SDinesh E(2024)An effective video inpainting technique using morphological Haar wavelet transform with krill herd based criminisi algorithmScientific Reports10.1038/s41598-024-66496-x14:1Online publication date: 5-Jul-2024
https://doi.org/10.1038/s41598-024-66496-x

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