Humans recognize a multitude of objects in images with little effort, despite the fact that the image of the objects may vary somewhat in different view points, in many different sizes and scales or even when they are translated or rotated.
Objects can even be recognized when they are partially obstructed from view.
This task is still a challenge for computer vision systems.
Genetic algorithms can operate without prior knowledge of a given dataset and can develop recognition procedures without human intervention.
A recent project achieved 100 percent accuracy on the benchmark motorbike, face, airplane and car image datasets from Caltech and 99.4 percent accuracy on fish species image datasets.