Matlab is a registered trademark of The Mathworks, Inc.


 Advanced Source Code . Com

 
 
HOME SOURCE CODE SOFTWARE INFO SUPPORT CONTACT US
 
Source code for fingerprint recognition, face recognition and much more


Software Info    About us     
Go To Python Official Website

.: Click here to download :.

.: Click here to watch a video tutorial :.

Eigenfaces is the name given to a set of eigenvectors when they are used in the computer vision problem of human face recognition. The approach of using eigenfaces for recognition was developed by Sirovich and Kirby and used by Matthew Turk and Alex Pentland in face classification.The eigenvectors are derived from the covariance matrix of the probability distribution over the high-dimensional vector space of face images. The eigenfaces themselves form a basis set of all images used to construct the covariance matrix. This produces dimension reduction by allowing the smaller set of basis images to represent the original training images. Classification can be achieved by comparing how faces are represented by the basis set.

We have developed a fast and reliable Python code for face recognition based on Principal Component Analysis (PCA). Proposed algorithm results computationally inexpensive and it can run also in a low-cost pc such as Raspberry PI.

Requirements: Python 2.7, Numpy, PIL, Tkinter.

Index Terms: Python, face, recognition, PCA, Principal Component Analysis, Raspberry PI.

 

 

 

 

 

Figure 1. Face recognition



A simple and effective source code for Python Face Recognition.



Watch a video tutorial. Python 2.7, Numpy, PIL, Tkinter are required.

Release
Date
Major features
1.0

2018.06.27



We recommend to check the secure connection to PayPal, in order to avoid any fraud.
This donation has to be considered an encouragement to improve the code itself.

Python Face Recognition - Click here for your donation. In order to obtain the source code you have to pay a little sum of money: 30 EUROS (less than 42 U.S. Dollars).

Once you have done this, please email us luigi.rosa@tiscali.it
As soon as possible (in a few days) you will receive our new release of Python Face Recognition.

Alternatively, you can bestow using our banking coordinates:
Name :
Luigi Rosa
Address :
Via Pozzo Strada 5 10139 Torino Italy
Bank name:
Poste Italiane
Bank address:
Viale Europa 190 00144 Roma Italy
IBAN (International Bank Account Number) :
IT-50-V-07601-03600-000058177916
BIC (Bank Identifier Code) :
BPPIITRRXXX

All the code provided is written in Python language (.py files), with no compiled or other protected parts of code (executables). The code was developed with Python 2.7. The code provided has to be considered "as is" and it is without any kind of warranty. The authors deny any kind of warranty concerning the code as well as any kind of responsibility for problems and damages which may be caused by the use of the code itself including all parts of the source code.

New - Python Face Recognition
 Biometric Authentication with Python We have developed a fast and reliable Python code for face recognition based on Principal Component Analysis (PCA). Proposed algorithm results computationally inexpensive and it can run also in a low-cost pc such as Raspberry PI.
 
New - Raspberry PI Remote Desktop
 Raspberry PI Remote Desktop A complete and detailed PDF tutorial to learn how to connect to and from a Raspberry PI using Remote Desktop.
 
New - Speaker Verification System
 Text-Independent Speaker Authentication There are two major applications of speaker recognition technologies and methodologies. If the speaker claims to be of a certain identity and the voice is used to verify this claim, this is called verification or authentication.
 
New - Java Face Recognition
 Java-based Biometric Authentication System Face recognition is essential in many applications, including mugshot matching, surveillance, access control and personal identification, and forensic and law enforcement applications.
 
New - White Papers
 High Capacity Wavelet Watermarking Using CDMA Multilevel Codes This paper proposes a technique based on CDMA and multilevel coding in order to achieve a high capacity watermarking scheme. The bits of watermark are grouped together and for each sequence a different modulation coefficient is used.
 
New - WebCam Face Identification
 Face Recognition Based on Fractional Gaussian Derivatives Local photometric descriptors computed for interest regions have proven to be very successful in applications such as wide baseline matching, object recognition, texture recognition, image retrieval, robot localization, video data mining, building panoramas, and recognition of object categories.
 
New - Speaker Recognition System
 Source code for speaker recognition
Speaker recognition is the process of automatically recognizing who is speaking on the basis of individual information included in speech waves.
 
New - Speech Recognition System
 Source code for isolated words recognition
Speech recognition technology is used more and more for telephone applications like travel booking and information, financial account information, customer service call routing, and directory assistance. Using constrained grammar recognition, such applications can achieve remarkably high accuracy.
 



The MathWorks, Inc. Google NeuralNetworks.It Octave Scilab The R Project for Statistical Computing Python Other available resources English Dictionary Download .Com
 
Software Info    About us