To get full information or details of face recognition using pca please have a look on the pages

http://seminarsprojects.net/Thread-Human-Face-Recognition-Using-PCA-on-Wavelet-Subband

http://seminarsprojects.net/Thread-Face-Recognition-using-Principal-Component-Analysis--44427

http://seminarsprojects.net/Thread-FACE-RECOGNITION-USING-PRINCIPAL-COMPONENT-ANALYSIS?pid=90032

if you again feel trouble on face recognition using pca please reply in that page and ask specific fields in face recognition using pca ....etc

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A NOVEL REPLICA DETECTION SYSTEM USING
BINARY CLASSIFIERS, R-TREES, AND PCA



ABSTRACT

Replica detection is a prerequisite for the discovery of copyright infringement
and detection of illicit content. For this purpose, contentbased
systems can be an efficient alternative to watermarking. Rather
than imperceptibly embedding a signal, content-based systems rely
on image similarity. Certain content-based systems use adaptive
classifiers to detect replicas. In such systems, a suspect image is
tested agai ....etc

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To get full information or details of digital video watermarking based on pca please have a look on the pages

http://seminarsprojects.net/Thread-mpeg-video-watermarking-technologies-techniques-and-issues

http://seminarsprojects.net/Thread-digital-video-watermarking-project

http://seminarsprojects.net/Thread-digital-video-watermarking-project?pid=111860

http://seminarsprojects.net/Thread-video-watermarking-using-integer-to-integer-discrete-wavelet-transform

if you again feel trouble on digital video watermarking based on pca please reply ....etc

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Principle Component Analysis PCA is a classical feature extraction and data representation technique
widely used in pattern recognition. It is one of the most successful techniques in face recognition. But it has
drawback of high computational especially for big size database. This paper conducts a study to optimize
the time complexity of PCA (eigenfaces) that does not affects the recognition performance. The authors
minimize the participated eigenvectors which consequently decreases the computational time. A
comparison is done to compare ....etc

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i need matlab code for digital video watermarking using dwt and pca ....etc

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IM A FINAL YEAR STUDENT DOING ME - APPLIED ELECTRONICS ,IM DOING PROJECT RELATED TO BREAST CANCER.THUS I WANTED TO KNOW HOW SVM AS A CLASSIFIER AND PCA AS A FEATURE EXTRACTOR WORKS. ....etc

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I want matlab code to apply PCA on KDDCUP 99 for feature reduction ....etc

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Plz, help me with the PCA code for doing image fusion. i need the program with an example. i tried for cameraman image but getting the output as complete black. i blurred it at two different places so i hav i1 n i2 which are blurred images which i converted to zero mean images i_1 n i_2.This is my program. what to do next?

clc;
close all;
clear all;
f1=imread('cameraman.tif');
figure(1);
imshow(f1);
=size(f1);
f1=im2double(f1);
level=input('enter the level of blur');
degradation=fspecial('average',);
i1=f1;
....etc

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to get information about the topic face recognition technology full report ppt, and related topics refer the page link bellow

http://seminarsprojects.net/Thread-face-recognition-technology-a-seminars-report

http://seminarsprojects.net/Thread-face-recognition-technology-a-seminars-report?page=4

http://seminarsprojects.net/Thread-seminars-report-on-face-recognition-technology

http://seminarsprojects.net/Thread-FACE-RECOGNITION-TECHNOLOGY-SEMINAR-REPORT--28533

http://seminarsprojects.net/Thread-face-recognition-technology--27390

http://semin ....etc

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Abstract

Face recognition is taken into account to be some of the dependable biometric, when safety points are taken into concern. For this, function extraction turns into a crucial drawback. Different strategies are used for extraction of facial function that are broadly categorized into linear and nonlinear subspaces. Among the linear strategies are Linear Discriminant Analysis (LDA), Bayesian Methods (MAP and ML), Discriminative Common Vectors (DCV), Independent Component Analysis (ICA), Tensor faces Multi-Linear Singular Value Decompositio ....etc

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