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            The local binary pattern (LBP) operator is defined as a gray-scale invariant texture measure, 
  derived from a general definition of   texture in a local neighborhood. Through its recent extensions, 
  the LBP operator has been made into a really powerful measure of image texture, showing excellent results 
  in many empirical studies. The LBP operator can be seen as a unifying approach to the traditionally divergent 
  statistical and structural models of texture analysis. Perhaps the most important property of the LBP operator 
  in real-world applications is its invariance against monotonic gray level changes. Another equally important 
  is its computational simplicity, which makes it possible to analyze images in challenging real-time settings.  
  The LBP method and its variants have already been used in a large number of applications all over the world.
  The LBP is a non-parametric kernel which summarizes the local spacial structure of an image. Moreover, 
  it is invariant to monotonic gray-scale transformations, hence the LBP representation may be less sensitive 
  to changes in illumination. This is a very interesting property in iris recognition.
  Iris-based personal identification has attracted much attention in recent years. Almost all the 
  state-of-the-art iris recognition algorithms are based on statistical classifier and local image features, 
  which are noise sensitive and hardly to deliver perfect recognition performance. We have developed a novel iris 
  recognition method, using the histogram of local binary pattern for global iris texture representation 
  and classification.
        Index Terms: Matlab, source, code, iris, recognition, segmentation, detection, verification, matching, lbp, local, binary, pattern, histogram.
            
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 Figure 1. Local binary pattern histogram | ||||||||||||||
| A simple and effective source code for Iris Recognition Based On Local Binary Pattern. | |||||||||||||||
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                        Demo code (protected
                        P-files) available for performance evaluation. Matlab Image Processing Toolbox is required. | |||||||||||||||
| Release | Date | Major features | |||||||||||||
| 1.0 | 2025.02.03 | 
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| 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. | |||||||||||||||
| 
                        Iris Recognition Based On Local Binary Pattern - Click here for
                        your donation. In order to obtain the source code you 
                        have to pay a little sum of money: 150 EUROS (less 
                        than 210 U.S. Dollars). | |||||||||||||||
| Once you have done this, please email us [email protected] As soon as possible (in a few days) you will receive our new release of Iris Recognition Based On Local Binary Pattern. Alternatively, you can bestow using our banking coordinates: 
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            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 2006a. Matlab Image Processing Toolbox is 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.
            






 
  
  
  
 
           
          
