I am doing an iris recognition project. Up to now,I have done iris normalization.
After normalization of iris, the next step is feature encoding of the normalized iris image. I have searched a lot but I didn't really understand feature encoding in iris recognition. So I put the code for the normalization part below.
The output image for the code:
image = cv2.imread('iris_masked.jpg')
center = (circles[0][0][0], circles[0][0][1])
iris_radius = radiusall-radiuspupil
nsamples = 360.0
samples = np.linspace(0,2.0 * np.pi, nsamples)[:-1]
polar = np.zeros((iris_radius, nsamples))
for r in range(iris_radius):
for theta in samples:
x = (r+radiuspupil) * np.cos(theta) + center[0]
y = (r+radiuspupil) * np.sin(theta) + center[1]
polar[r][theta * nsamples / 2.0 / np.pi] = image[y][x][0]
cv2.imwrite('normalized.jpg', polar)
plt.imshow(polar, cmap = 'gray', interpolation = 'bicubic')
plt.xticks([]), plt.yticks([])
plt.show()
How should I continue from where I left in order to do feature encoding?
