Personal Authentication Based on Iris Texture Analysis
Â¢ Biometric-based personal verification and identification
methods have gained much interest with an increasing emphasis on
security. Iris recognition is a fast, accurate and secure biometric
technique that can operate in both verification and identification
modes since the iris texture pattern has no links with the genetic
structure of an individual and since it is generated by chaotic
Â¢ In this paper, we present a method for iris recognition based
on a wavelet packet decomposition of iris images.
Â¢ Each iris image is described by a subset of band-filtered
images (sub images) containing wavelet coefficients. From these
coefficients, which characterize the iris texture, we compute a compact
iris feature code using the appropriate energies of these sub images to
generate binary iris codes according to an adapted threshold.
Â¢ Thereafter, we show how an efficient and reliable Hamming
distance can be used in order to classify iris codes. Results are
presented that demonstrate significant improvements in iris recognition
accuracy through the use of the public iris database CASIA.
Â¢ Existing is done using Finger printing .Finger printing is that
much not flexible because we can make duplicates of fingers and bluff
people. It is not that much efficient.
Â¢ Only the spatial domain is calculated.
Â¢ We will be using PCA i.e. Principal Component Analysis
algorithm to find out co-variance and variance.
Â¢ Spatial domain is not efficient in calculating the edge parts
of the image.
Â¢ In the proposed system we will be using DWT i.e Discrete
Â¢ In DWT we can divide the image into different sub-band levels.
Â¢ We can get information of approximate coefficient and edge
coefficients. By this we can efficiently compare the edges.
Strengths Vs Weakness
Â¢ Finding the wavelet transformation for each pixel.
Â¢ Spatial domain to frequency domain makes the system much
Â¢ Usually the RGB values are converted into the gray levels for
the further comparisons. But directly we are not dealing with RGB
images, this can be improved.