dc.contributor.author |
Kotiyal, Bandanawaz |
|
dc.contributor.author |
Kazmi, Md. Nasrullah (14DET50) |
|
dc.contributor.author |
Faiz, Mohd (12ET77) |
|
dc.date.accessioned |
2017-05-19T06:00:55Z |
|
dc.date.available |
2017-05-19T06:00:55Z |
|
dc.date.issued |
2017-05 |
|
dc.identifier.uri |
http://www.aiktcdspace.org:8080/jspui/handle/123456789/1964 |
|
dc.description.abstract |
Individual recognition using Iris is most commonly employed in all place.
This requires some special cameras to take the Iris image and the obtained iris
images were classified based on the features extracted. Only identification of
person is not the application of Iris recognition. It can be developed to do many
process.The iris image captured from the cameras were taken. Individual
recognition using Iris is most commonly employed in all place. In the proposed
approach the process of recognition of the persons based on Iris image is
employed. The recognition of iris is done based on the DWT features extracted
from iris image. The DWT features were the statistical features extracted from the
input images. The extracted features were optimized based on Genetic algorithm.
The genetic algorithm process includes selection, crossover and mutation process.
The probability of the selection of the features were estimated in the selection,
cross over and the mutation process. The optimized features were then used for
matching process based on Euclidean distance measurement. Before the extraction
of the features preprocessing in the iris images were employed based on the
smoothening process and the edge detection process. The preprocessed iris image
is then normalized. The normalization process identifies the iris and pupil region in
the image correctly and it reshapes the identified positions. The normalization
process improves the efficiency. The process of application of the optimization
techniques helps in the reduction of the feature counting. The person to whom the
input iris belongs is identified and with the help of the identified person the
matching process is employed. The performance of the process is measured based
on the performance metrics. The performance of the process measured indicates
that the proposed approach is more improved compared to the other existing
approaches for the iris recognition process. |
en_US |
dc.language.iso |
en_US |
en_US |
dc.publisher |
AIKTC |
en_US |
dc.relation.ispartofseries |
Accession # PE0176; |
|
dc.subject |
Project Report - EXTC |
en_US |
dc.title |
IRIS recognition system using MATLAB |
en_US |
dc.type |
Project Report |
en_US |