Generalized Dynamic Morphological Quotient Image
By Sanghun Lee (Google Scholar, Website)
Yonsei Univ.
This repository contains a Matlab implementation of "Multiscale morphology based illumination normalization with enhanced local textures for face recognition" (http://dx.doi.org/10.1016/j.eswa.2016.06.039) (pdf)
- We converted the original version of GDMQI written in C++ (using OpenCV) into this Matlab version.
- It is not optimized version.
- Only 'Cropped version of Extended Yale-B database' was tested.
- Download and unzip 'Cropped version of Extended Yale-B database' (Link)
- Open 'main.m' file
- Modify DB_LOCATION to specify the database location, (ex. DB_LOCATION = 'D:\Database\YaleB';)
- run
If you use GDMQI in your research, please cite:
@article{lee2016multiscale,
title={Multiscale morphology based illumination normalization with enhanced local textures for face recognition},
author={Lee, Sanghun and Lee, Chulhee},
journal={Expert Systems with Applications},
volume={62},
pages={347--357},
year={2016},
publisher={Elsevier}
}