- Ant Colony Optimization (ACO) Image Feature Extraction Method
Feature Extraction and Feature Selection are two different tasks. Feature Extraction is initial and vital step, but feature selection is optional. There are lots of evolutionary feature selection code are online for MATLAB but not feature extraction, especially for image. This code extracts features out of 10 classes of images with Ant Colony Optimization (ACO) evolutionary algorithm and compared it with extracted features using SURF with KNN classifier. Dataset is consists of 100 samples of small objects in 10 classes. You can use your data but labeling is done manually which you have to change it. following parameters are so important which you have to play with them in order to get desired results. Parameters are: 'nf', 'MaxIt', 'nAnt', knn classifier neighbors and number of hidden layers in "TrainNN.m" file.
- Email: mosavi.a.i.buali@gmail.com
- Author: Seyed Muhammad Hossein Mousavi
- My MathWorks: https://www.mathworks.com/matlabcentral/profile/authors/9763916
- My GitHub: https://github.com/SeyedMuhammadHosseinMousavi
% Hope it help you (Be Happy :)
