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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Face Recognition using the Techniques Base on Principal Component Analysis (PCA)

several past few years, Face Recognition has become more significant. Although, other identification methods such as Fingerprints or Iris recognition are currently in use, face recognition has its own application.

Principal Component Analysis (PCA) has been variously used in pattern recognition applications, especially in face recognition field. In this seminars, several techniques based on standard PCA, Fisher Linear ....etc

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Principal Component Analysis
• PCA is a powerful tool for analyzing data.
• It is a way of identifying patterns in data, and expressing the data in such a way as to highlight their similarities and differences.
• Principal component analysis (PCA) involves a mathematical procedure that transforms a number of possibly correlated variables into a smaller number of uncorrelated variables called principal components.
• Principal Components Analysis is a method that reduces data dimensionality by performing a c ....etc

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i want to ppt on ct & mri image using curvelet transform
so please send me
on my mail id
[email protected] ....etc

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Hi am rohan I would like to get source code for PCA image fusion matlab code.  i saw this site while searching for code. I'm living at kolkata and now I need help on PCA source code please do provide as soon as possible ....etc

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Abstract
Together with the growing interest in the development of human and computer interface and
biometric identification, human face recognition has become an active research area since early
90. Nowadays, Principal Component Analysis (PCA) has been widely adopted as the most
promising face recognition algorithm. Yet still, PCA has its limitations: poor discriminatory power
and large computational load.
In view of these limitations, this paper proposed a new approach in using PCA - apply PCA on
wavelet subband. Traditionally, ....etc

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send me face recognition using pca full report


prajakta ....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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During several past few years, Face Recognition has become more significant. Although, other identification methods such as Fingerprints or Iris recognition are currently in use, face recognition has its own application. Principal Component Analysis (PCA) has been variously used in pattern recognition applications, especially in face recognition field. In this seminars, several techniques based on standard PCA, Fisher Linear Discriminant (FLD), Face Specific Subspace (FSS) will be discussed. We will review the developed idea used in the 2D-PCA ....etc

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....etc

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