PSO LPQ Image Features
%% PSO-LPQ Image Features - Created in 22 Jan 2022 by Seyed Muhammad Hossein Mousavi
% This code extracts Local Phase Quantization (LPQ) features out of 100
% samples of images in 10 classes. LPQ features are in the family of frequency based features.
% Then desired number of PSO features
% will be selected out of extracted LPQ features which have highest
% impact. Actually, you can select n strongest features. Results show,
% however number of selected features goes down, but recognition accuracy
% is almost intact. 'nf' is number of selected features by PSO. Images are
% stores in 'data' folder.
% ------------------------------------------------
% Feel free to contact me if you find any problem using the code:
% Author: SeyedMuhammadHosseinMousavi
% My Email: mosavi.a.i.buali@gmail.com
% My Google Scholar: https://scholar.google.com/citations?user=PtvQvAQAAAAJ&hl=en
% My GitHub: https://github.com/SeyedMuhammadHosseinMousavi?tab=repositories
% My ORCID: https://orcid.org/0000-0001-6906-2152
% My Scopus: https://www.scopus.com/authid/detail.uri?authorId=57193122985
% My MathWorks: https://www.mathworks.com/matlabcentral/profile/authors/9763916#
% my RG: https://www.researchgate.net/profile/Seyed-Mousavi-17
% ------------------------------------------------
% Hope it help you, enjoy the code and wish me luck :)
-
Notifications
You must be signed in to change notification settings - Fork 0
PSO LPQ Image Features
License
SeyedMuhammadHosseinMousavi/PSO-LPQ-Image-Features
This commit does not belong to any branch on this repository, and may belong to a fork outside of the repository.
Folders and files
Name | Name | Last commit message | Last commit date | |
---|---|---|---|---|
Repository files navigation
About
PSO LPQ Image Features
Topics
Resources
License
Stars
Watchers
Forks
Releases
No releases published
Packages 0
No packages published