Daugman implementation to segement iris and pupil
Project description
irisSeg
Segementation of iris and pupil.
Daugman algorithm:
where I(x,y) is the eye image, r is the radius to searches over the image (x,y), G(r) is a Gaussian smoothing function. The algorithm starts to search from the pupil, in order to detect the changing of maximum pixel values (partial derivative).
Installation
pip install irisSeq
Usage
from irisSeg import irisSeg
import matplotlib.pyplot as plt
#
# you can also view using the argument in irisSeq function
#
coord_iris, coord_pupil, output_image = irisSeg('UBIRIS_200_150_R/Sessao_1/1/Img_1_1_1.jpg', 40, 70)
print(coord_iris)
print(coord_pupil)
plt.imshow(output_image)
plt.show()
References
https://www.diva-portal.org/smash/get/diva2:831173/FULLTEXT01.pdf
https://uk.mathworks.com/matlabcentral/fileexchange/15652-iris-segmentation-using-daugman-s-integrodifferential-operator
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
irisSeg-0.1.tar.gz
(6.0 kB
view hashes)
Built Distributions
irisSeg-0.1-py3-none-any.whl
(8.0 kB
view hashes)
Close
Hashes for irisSeg-0.1-py2.py3-none-any.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | 372005986ec6096d1b47240c51e364cb66cc75041c5e0500754b4694fb0605e4 |
|
MD5 | 95aa62626c6d8650183176294da319dd |
|
BLAKE2b-256 | eca7387dbc486fa4698e105f850757c2e3dbb8078da6a4d0dca6051cb8e83898 |