Processed Histogram based Face Recognition 1.0

Operating systemsOS : Windows / Linux / Mac OS / BSD / Solaris
Program licensingScript Licensing : BSD - BSD License
CreatedCreated : May 10, 2010
Size downloadDownloads : 5
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It has an accuracy of 99.75%.<br />Recognizing ...

It has an accuracy of 99. 75%.
Recognizing objects from large image databases, histogram based methods have proved simplicity and usefulness in last decade.
Initially, this idea was based on color histograms that were launched by swain. This algorithm presents the first part of our proposed technique named as “ Histogram processed face_recognition
For training, grayscale images with 256 gray levels are used. Firstly, frequency of every gray-level is computed and stored in vectors for further processing.
Secondly, mean of consecutive nine frequencies from the stored vectors is calculated and are stored in another vectors for later use in testing phase.
This mean vector is used for calculating the absolute differences among the mean of trained images and the test image.
Finally the minimum difference found identifies the matched class with test image.
recognition accuracy is of 99. 75% (only one mis-match i. e. recognition fails on image number 4 of subject 17).
Demands:
• MATLAB 7. 4 or higher
• MATLAB's Image Processing Toolbox

Processed Histogram based Face Recognition 1.0 scripting tags: images, stored, histogram algorithm, recognition, face recognition, test, object recognition, vectors. What is new in Processed Histogram based Face Recognition 1.0 software script? - Unable to find Processed Histogram based Face Recognition 1.0 news. What is improvements are expecting? Newly-made Processed Histogram based Face Recognition 1.1 will be downloaded from here. You may download directly. Please write the reviews of the Processed Histogram based Face Recognition. License limitations are unspecified.