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

[:=Read Full Message Here=:]

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

[:=Read Full Message Here=:]

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

[:=Read Full Message Here=:]

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

[:=Read Full Message Here=:]

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

[:=Read Full Message Here=:]

....etc

[:=Read Full Message Here=:]

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

[:=Read Full Message Here=:]

send me face recognition using pca full report


prajakta ....etc

[:=Read Full Message Here=:]

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

[:=Read Full Message Here=:]

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

[:=Read Full Message Here=:]