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 Matlab Official Website

.: Click here to download :.

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. They are distinctive, robust to occlusion, and do not require segmentation. Recent work has concentrated on making these descriptors invariant to image transformations. The idea is to detect image regions covariant to a class of transformations, which are then used as support regions to compute invariant descriptors.

The fractional gaussian derivative can be computed in a number of ways, one such way is in the frequency domain. Denoting the Fourier transform of the function f(x) as F(w), it is straight-forward to show that the Fourier transform of the nth-order derivative, f(n)(x), is (jw)^n*F(w), for any integer order n. Of course, there is no reason why n must be an integer, n can be any real (or complex) number - hence the fractional derivative.

The code has been tested with AT&T database achieving an excellent recognition rate of 99.60% (40 classes, 5 training images and 5 test images for each class, hence there are 200 training images and 200 test images in total randomly selected and no overlap exists between the training and test images).

Index Terms: Matlab, source, code, face recognition, webcam, local descriptors, web cam, fractional gaussian derivatives, face matching, face identification.

 

 

 

 

 

Figure 1. 2D Gaussian and Derivatives



A simple and effective source code for WebCam Face Identification.



Demo code (protected P-files) available for performance evaluation. Matlab Image Processing Toolbox and Matlab Image Acquisition Toolbox are required.

Release
Date
Major features
2.0

2007.09.27

1.0

2007.08.23

  • Face recognition based on fractional gaussian derivatives
  • High recognition rate: 99.40% using AT&T Database
  • Easy and intuitive GUI
  • Command line functions for rapid testing
  • Webcam image acquisition


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.

WebCam Face Identification - Release 1.0 - Click here for your donation. In order to obtain the source code you have to pay a little sum of money: 600 EUROS (less than 840 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 WebCam Face Identification.

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

The authors have no relationship or partnership with The Mathworks. All the code provided is written in Matlab language (M-files and/or M-functions), with no dll or other protected parts of code (P-files or executables). The code was developed with Matlab 14 SP1. Matlab Image Processing Toolbox and Matlab Image Acquisition Toolbox are required. 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