Iris-Recognition | An Iris recognition system , implemented in Matlab | Machine Learning library

by thuyngch Python Version: Current License: MIT

X-Ray Key Features Code Snippets Community Discussions(1)Vulnerabilities Install Support

kandi X-RAY | Iris-Recognition Summary

Iris-Recognition is a Python library typically used in Artificial Intelligence, Machine Learning applications. Iris-Recognition has no bugs, it has no vulnerabilities, it has a Permissive License and it has low support. However Iris-Recognition build file is not available. You can download it from GitHub.

I have made Iris-Recognition system, implemented in both Matlab and Python. ## Keyword: Iris Recognition, Biometrics, Computer Vision, Image Processing, Daugman.

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Iris-Recognition has a low active ecosystem.

It has 85 star(s) with 64 fork(s). There are 10 watchers for this library.

It had no major release in the last 6 months.

There are 9 open issues and 6 have been closed. On average issues are closed in 5 days. There are 1 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of Iris-Recognition is current.

Quality

Iris-Recognition has 0 bugs and 28 code smells.

Security

Iris-Recognition has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

Iris-Recognition code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

Iris-Recognition is licensed under the MIT License. This license is Permissive.

Permissive licenses have the least restrictions, and you can use them in most projects.

Reuse

Iris-Recognition releases are not available. You will need to build from source code and install.

Iris-Recognition has no build file. You will be need to create the build yourself to build the component from source.

Installation instructions are not available. Examples and code snippets are available.

It has 1117 lines of code, 35 functions and 19 files.

It has low code complexity. Code complexity directly impacts maintainability of the code.

Top functions reviewed by kandi - BETA

kandi has reviewed Iris-Recognition and discovered the below as its top functions. This is intended to give you an instant insight into Iris-Recognition implemented functionality, and help decide if they suit your requirements.

Extract feature from an image
Generate the QR code for the Gabor filter
Perform the convolution of the image
Normalize an image
Calculates the Hamming distance for a given template
Calculate the Hamming distance
Shift bits by noshifts
Extract a matrix from a file
Extract a feature from an image
Calculates the Hamming distance matching
Function to extract a feature
Calculate the hamming distance between two templates

Get all kandi verified functions for this library.

Iris-Recognition Key Features

No Key Features are available at this moment for Iris-Recognition.

Iris-Recognition Examples and Code Snippets

No Code Snippets are available at this moment for Iris-Recognition.

Community Discussions

Trending Discussions on Iris-Recognition

Iris-recognition System OpenCV

QUESTION

Iris-recognition System OpenCV

Asked 2020-Apr-30 at 11:44

I've been searching for iris recognition implementations. I just see Matlab implementations only. why python doesn't have while python has more extensive and mature libraries?

How can I create my own iris-recognition system? can you help to define the road map?

...

ANSWER

Answered 2020-Apr-30 at 11:44

Now that we know the problem:

The first step is to find implement-ready codes, i recommend you to take a look at these:

then if the codes above did not help (which is highly unusual), you have to make these steps:

first search the available papers in this field, see the designs
if you like to implement the pipeline via neural networks
1. train a CNN network in Tensorflow
2. port it into OpenCV for compatibility with every device, take a look at this link for example
if you like to develop your algorithm via hand-customed algorithms, i highly recommend following a paper, this way is richly researched in the literature and is mature.

hopefully this helps.

Source https://stackoverflow.com/questions/61490080

Community Discussions, Code Snippets contain sources that include Stack Exchange Network

Vulnerabilities

No vulnerabilities reported

Install Iris-Recognition

You can download it from GitHub.
You can use Iris-Recognition like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.

Support

For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .

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