iris recognition by curvelet transform and hamming distance

Description

In this code we use 400 iris image in training and test.

Feature extraction is based on curvelet transform

Classification is based on hamming distance.

related papers :

Sathiyaraja, K., M. Dhineshkumar, and N. Thiyagarajan. “Iris Segmentation and Recognization Using Log Gabor Filter and Curvelet Transform.” International Journal Of Engineering And Computer Science 2.9 (2013): 2709-2714.
9 ijecs

Ahamed, Afsana, and Mohammed Imamul Hassan Bhuiyan. “Low complexity iris recognition using curvelet transform.” Informatics, Electronics & Vision (ICIEV), 2012 International Conference on. IEEE, 2012.
ahamed2012

Ma, Jianwei, and Gerlind Plonka. “The curvelet transform.” Signal Processing Magazine, IEEE 27.2 (2010): 118-133.

CurveletTransform
Sun, Jie, Zhe-Ming Lu, and Lijian Zhou. “Iris Recognition using curvelet transform based on principal component analysis and linear discriminant analysis.” J Inf Hiding Multimedia Signal Process 5.3 (2014): 567-573.

guesmi2012
Umer, Saiyed, Bibhas Chandra Dhara, and Bhabatosh Chanda. “Iris recognition using multiscale morphologic features.” Pattern Recognition Letters 65 (2015): 67-74.

umer2015

first run

step1_algorithm_generate_DATA1\start1.m

to generate DATA1.mat

then copy it to current folder

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main code is

new_curvelet1_hamming20.m