How to create feature vector ?

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Explorer
Explorer 2013-10-7
编辑： Walter Roberson 2014-1-30
Someone suggested me to do as follows:
"take the histogram and construct a feature vector that has several comparison metrics, such as mean, std dev, skewness, range, RMS difference, and median absolute difference. Then compare feature vectors to see which are closest "
I have tried to do so which is mentioned below.
clear all; close all; clc;
im1=imread('106a.jpg');
im2=imread('107a.jpg');
im1g=rgb2gray(im1);
im2g=rgb2gray(im2);
%%Calculating mean of im1
grayImage=rgb2gray(im1);
subplot(1, 2, 1);
imshow(grayImage, []);
title('Original Grayscale Image');
set(gcf, 'Position', get(0,'Screensize')); % Enlarge figure to full
%screen.
% Let's get its histogram.
[pixelCount grayLevels] = imhist(grayImage);
subplot(1, 2, 2);
bar(pixelCount);
title('Histogram of original image');
xlim([0 grayLevels(end)]); % Scale x axis manually.
yRange = ylim;
% Calculate the mean gray level
meanGL = sum(pixelCount .* grayLevels) / sum(pixelCount)
%%Calculating mean of im2
grayImage2=rgb2gray(im2);
figure, subplot(1, 2, 1);
imshow(grayImage2, []);
title('Original Grayscale Image');
set(gcf, 'Position', get(0,'Screensize')); % Enlarge figure to full
%screen.
% Let's get its histogram.
[pixelCount2 grayLevels2] = imhist(grayImage2);
subplot(1, 2, 2);
bar(pixelCount2);
title('Histogram of original image');
xlim([0 grayLevels2(end)]); % Scale x axis manually.
yRange2 = ylim;
% Calculate the mean gray level
meanGL2 = sum(pixelCount2 .* grayLevels2) / sum(pixelCount2)
%%Calculating standard deviation
st_d1=std(double(im1));
st_d2=std(double(im2));
%%Calculating Skewness
sk1=skewness(double(im1));
sk2=skewness(double(im2));
%%Calculating RMS
rms1=rms(im1);
rms2=rms(im2);
%%Calculating median absolute
md1=mad(double(im1));
md2=mad(double(im2));
%%Contruct a feature vector
fv1=[ meanGL, st_d1, sk1, rms1, md1 ]
fv2= [ meanGL2, st_d2, sk2, rms2, md2 ]
But it seems like I have not created feature vectors correctly because of reasons:
1. dimensions of meanGL, st_d1, sk1, rms1 and md1 are different. 2. after evaluating above code in MATLAB editor, I am getting error
" Error using horzcat
Dimensions of matrices being concatenated are not consistent.
Error in oct6 (line 71)
fv1=[ meanGL, st_d1, sk1, rms1, md1 ] ; "
But it

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采纳的回答

saranya
saranya 2014-1-30
As u have converted the image to gray scale it gives the 1D matrix.. so u get the "hor concate" error... try changing this code for the part of calculating mean and try u will the result..
%%Calculating mean of im1
grayImage=rgb2gray(im1);
meanGL = mean(im1);
now u will get the feature vector... for clarification see
size(meanGL)
size(st_d1)
size(sk1)
size(rms1)
size(md1)
see this value for ur previous coding and this coding..

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