APPLICATION OF GENETIC ALGORITHM FOR IMAGE TRANSFER

2020 ◽  
Vol 1 (2) ◽  
pp. 44-51
Author(s):  
Paula Pereira ◽  
Tanara Kuhn
Keyword(s):  
Genetic Algorithm ◽  
Lossless Compression ◽  
Search Method ◽  
Source Image ◽  
Image Transfer ◽  
Target Image ◽  
Mosaic Image ◽  
Permutation Array

For images transfer, different embedding system exist which works by creating a mosaic image from the source image and recovery from the target image using some sort of algorithm. In current study, a method is proposed using the genetic algorithm for recovery of image from the source image. The algorithm utilized is genetic algorithm which is a search method along with another additional technique for obtaining higher robustness and security. The proposed methodology works by dividing the source image into smaller parts which are fitted into target image using the lossless compression. The mosaic image is recovered at retrieving side by the permutation array which is recovered and mapped using the pre-select key.

scholarly journals Comparison of Genetic Algorithm and Harmony Search Method for 2D Geometry Optimization.

2018 ◽  
Vol 159 ◽  
pp. 01009 ◽  
Author(s):  
Mohammad Ghozi ◽  
Anik Budiati
Keyword(s):  
Genetic Algorithm ◽  
Harmony Search ◽  
Geometry Optimization ◽  
Steel Structure ◽  
Search Method ◽  
Geometric Optimization ◽  
Computational Time ◽  
Time Required ◽  
Average Computational Time ◽  
Better Than

There are many applications of Genetic Algorithm (GA) and Harmony Search (HS) Method for solving problems in civil engineering design. The question is, still, which method is better for geometry optimization of a steel structure. The purpose of this paper is to compare GA and HS performance for geometric optimization of a steel structure. This problem is solved by optimizing a steel structure using GA and HS and then comparing the structure’s weight as well as the time required for the calculation. In this study, GA produced a structural weight of 2308.00 kg to 2387.00 kg and HS scored 2193.12 kg to 2239.48 kg. The average computational time required by GA is 607 seconds and HS needed 278 seconds. It concludes that HS is faster and better than GA for geometry optimization of a steel structure.

The Research of Image Registration Method Based on the Genetic Algorithm

2012 ◽  
Vol 182-183 ◽  
pp. 1916-1918
Author(s):  
Hua Li ◽  
Di Xiao Wu ◽  
Qing Min Li ◽  
Peng Ying Zhang ◽  
Rui Wang
Keyword(s):  
Remote Sensing ◽  
Genetic Algorithm ◽  
Image Registration ◽  
Satellite Remote Sensing ◽  
Search Method ◽  
Feature Point ◽  
Image Morphing ◽  
Registration Method ◽  
State Information

This paper puts forward one image registration method based on the feature point of the contour, and Introducing the search method based on genetic algorithm .the method can deal with image morphing caused by translation, rotation and zooming change. This method is simple, convenient , feasible and good robustness, and is suitable for the aerial of satellite remote sensing, the plane and UUV underwater detection state information which are rich image for registration.

Niching genetic algorithm adopting restricted competition selection combined with pattern search method

2002 ◽  
Vol 38 (2) ◽  
pp. 1001-1004 ◽  
Author(s):  
Jae-Kwang Kim ◽  
Dong-Hyeok Cho ◽  
Hyun-Kyo Jung ◽  
Cheol-Gyun Lee
Keyword(s):  
Genetic Algorithm ◽  
Search Method ◽  
Pattern Search ◽  
Pattern Search Method
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