Research Article
[Retracted] Image Encryption Algorithm Based on Artificial Bee Colony Algorithm and Chaotic System
Algorithm 2
Artificial bee colony optimization algorithm based on crossover operator.
| Require: Population: , Maximum number of iterations: , investigationsize, observationsize | | Ensure: Optimal encrypted image and its position | (1) | According to equation (13) | (2) | | (3) | Rearrange according | (4) | fordo | (5) | /Hiring bee stage/ | (6) | fordo | (7) | | (8) | | (9) | | (10) | | (11) | | (12) | Substitute into equation (4) to update its position | (13) | Boundary value processing | (14) | Search for the corresponding encrypted image according to | (15) | equation (13) which in | (16) | According to equation (5) for select the better individuals | (17) | end for | (18) | /Introducing crossover operator/ | (19) | Sort and save the top in | (20) | The remaining according to Figure 2 to cross other images | (21) | Calculate the fitness According to equation (13), select the better individuals according to equation (5) | (22) | /Observation bee stage/ | (23) | fordo | (24) | according to equation (6) | (25) | | (26) | | (27) | | (28) | | (29) | | (30) | | (31) | repeat 11–16 | (32) | end for | (33) | /Investigation bee stage/ | (34) | fordo | (35) | Judge whether to give up the honey source | (36) | end for | (37) | end for | (38) | Calculate the fitness of each encrypted image in , select the encrypted image with the maximum fitness, and return its corresponding position |
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