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Principal Component Analysis (PCA) on images in MATLAB (GUI)

version 1.0.4 (12.2 MB) by ABHILASH SINGH
Principal Component Analysis (PCA) on images in MATLAB (GUI)

19 Downloads

Updated 13 Mar 2020

GitHub view license on GitHub

First, upload a colour image by clicking on the “upload an image button”. The acceptable image formats are png, jpg, jpeg, img and tif. Then click on the "Plot the grayscale image". After that enter the no. of PC's up to which you want to retrieve the images (both colour and grayscale).
An error message/box will pop-up when you enter a number greater than the no. of PCs for that particular image. Also, an error will message will pop-up when the entered input is not a number.
Please go through this link for detail explanation;
https://medium.com/@abhilash.singh/principal-component-analysis-pca-on-images-in-matlab-a-graphical-user-interface-gui-3d4999ddd0d0

Enjoy!!!

Cite As

ABHILASH SINGH (2020). Principal Component Analysis (PCA) on images in MATLAB (GUI) (https://github.com/abhilash12iec002/Principal-Component-Analysis-PCA-on-images-in-MATLAB-GUI-), GitHub. Retrieved .

Comments and Ratings (1)

Bahut khoob.

Updates

1.0.4

Link update

1.0.3

https://medium.com/@abhilash.singh/principal-component-analysis-pca-on-images-in-matlab-a-graphical-user-interface-gui-3d4999ddd0d0

1.0.2

GitHub upload

1.0.1

Increases the no. of acceptable image format.

MATLAB Release Compatibility
Created with R2019b
Compatible with any release
Platform Compatibility
Windows macOS Linux
Acknowledgements

Inspired by: Real Time Object Detection using Deep Learning.