PSO + LPQ Image Features
PSO-LPQ-Image-Features
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 :)
Zitieren als
S. Muhammad Hossein Mousavi (2024). PSO + LPQ Image Features (https://github.com/SeyedMuhammadHosseinMousavi/PSO-LPQ-Image-Features), GitHub. Abgerufen .
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Version | Veröffentlicht | Versionshinweise | |
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1.0.0 |
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