Tamilnadu HSC Results 2012

The Tamilnadu Government announce HSC examination results are expected to be declared on May 22, 20.In below we put some 6 links for Tamilnadu +12 HSC Results 2012. So Students are check in below links.

dge1.tn.nic.in
dge2.tn.nic.in
dge3.tn.nic.in
tnresults.nic.in
results.nic.in
results.tamilnadueducation.net
www.examresults.net
www.schools9.com

above websites are publish the +12 exam results.

Related Search : Tamilnadu HSC Results 2012 ,Tamilnadu +12 HSC Results 2012 ,Tamilnadu +2 HSC Results may 22,2012,Tamilnadu Government HSC Results 2012.

RDWT Watermarking matlab code

Watermark Embedding Process

1. Apply RDWT (Redundant DWT) to original image
2.Apply SVD to the LL sub-band of Original image
 
3.Apply RDWT to the watermark image.

4.Apply SVD to the LL Sub-band of watermark image

5.Modify the singular values of the original image with the singular values of the watermark image

6.Apply inverse SVD on the transformed original image with modified singular values.

7.Apply inverse RDWT to obtain the watermarked image.

 Watermark Extraction Process

 1.Apply RDWT on the watermarked image.
2.Apply SVD to the LL sub-band of the watermarked image.
3.Extract the singular values of watermark image from the singular values of watermarked image and original image.

4.Apply inverse SVD
5.Apply inverse RDWT to obtain the watermark image.



Matlab code is given below


Embedding

clc
clear all
close all
warning off
alpha = 0.25;
input_img = imread('lena512.bmp'); % read input image
[LL,LH,HL,HH] = dwt2(input_img,'haar','mode','sym'); % applying  redundant DWT
[I_u,I_s,I_v] = svd(LL); % extract sigular values...
water_img = imread('cameraman.bmp'); % read watermark image
[WLL,WLH,WHL,WHH] = dwt2(water_img,'haar','mode','sym'); % applying  redundant DWT
[W_u,W_s,W_v] = svd(WLL); % extract sigular values...
S_n = I_s + (alpha*W_s); %Watermark Embedding
new_LL = I_u*S_n*I_v'; %Watermarked Image Construction
new_img = idwt2(new_LL,LH,HL,HH,'haar','mode','sym');
new_img=uint8(new_img);
imwrite(new_img,'Watermarked.bmp');

Extraction

clc
clear all
close all
warning off
alpha = 0.25;
water_img = imread('Watermarked.bmp'); % read watermarked image
[WMLL,WMLH,WMHL,WMHH] = dwt2(water_img,'haar','mode','sym'); % applying  redundant DWT
[Wm_u,Wm_s,Wm_v] = svd(WMLL); % extract sigular values...
input_img = imread('lena512.bmp'); % read input image
[LL,LH,HL,HH] = dwt2(input_img,'haar','mode','sym'); % applying  redundant DWT
[I_u,I_s,I_v] = svd(LL); % extract sigular values...
S_w= (Wm_s-I_s)/alpha; % Watermark extraction
watermark=imread('cameraman.bmp');
[WLL,WLH,WHL,WHH] = dwt2(watermark,'haar','mode','sym'); % applying  redundant DWT
[W_u,W_s,W_v] = svd(WLL); % extract sigular values...
new_WLL=W_u*S_w*W_v';
Watermark_img=idwt2(new_WLL,WLH,WHL,WHH,'haar','mode','sym');
Watermark_img=uint8(Watermark_img);
imwrite(Watermark_img, 'Watermark_img.bmp');

Related Search: Watermarking matlab code , Digital Watermarking RDWT matlab code ,SVD based Watermarking matlab code.Matlab watermark embedding and extraction.

Matlab Neural Network Watermarking Code

 Watermark Embedding

1. Divide the original image I into blocks of size 8X8 and perform three-level DWT transform on each block. Select the position of watermark embedding coefficient using random sequence with a secret key and quantize the DWT coefficient C(I,j) by Q and use that value as the input T of BPN.
2. Create the improved neural network and initialize its parameters, we use T as the supervised signal and the average of each block is used as the desired output value of the BPN to train BPN. Training error is set to be 0.001.
3. Perform the inverse discrete wavelet transform (IDWT) on the coefficients where the watermark is embedded to obtain the watermarked image.

Watermark Extraction

1. Perform the three-level DWT transformation on the watermarked image blocks.
2. Select the position of coefficient C(i, j), where watermark is embedded with the same secret key , which is used in watermark embedding sequence.
3. Quantize the DWT coefficient by Q, and use it as input value of the trained BPN to get the output T.
4. Extract the watermark according to (6) below using the output T and coefficient C(i ,j)

Matlab Automatic Vehicle Plate Recognition code

Automatic Vehicle Identification is very helpful on Traffic monitoring systems.Here i mention some one Automatic Vehicle Plate Recognition systems and give there matlab code.Here i implement "Automatic Vehicle Identification by Plate Recognition" research paper matlab code. This research paper do followings operations.

1. Read input image.
2. Converted into Binary image.
3. Then threshold based area removal using smearing algorithms.
4. Applying Morphological dilation and extract Plate area.
5. Finally apply segmentation to extract the characters.

 Matlab code and output as given below.

clc
clear all
close all
warning off

in_img = imread('input.JPG');
figure;imshow(in_img);
% Threshold based car parts removing...

bw_img = im2bw(in_img);
% imshow(bw_img);

hori_thresh = sum(bw_img,2);


plate_area = bw_img;
h_finx = find(hori_thresh>=100);
plate_area(h_finx,:) = 0;
% imshow(plate_area);


ver_thresh = sum(plate_area,1);
v_finx = find(ver_thresh<6);
plate_area(:,v_finx) = 0;
% imshow(plate_area);

% apply morphological operation and find the plate region
mor_img = bwmorph(plate_area,'dilate');
label_img = bwlabel(mor_img,4);
tot_labe1 = max(max(label_img));
plate_area = zeros(size(mor_img,1),size(mor_img,2));
plate_region = zeros(size(mor_img,1),size(mor_img,2));
for i = 1:tot_label
    [r c] = find(labe1_img==i);
    tot = length(r);
    if tot>1000
        for j = 1:length(r)
            plate_area(r(j),c(j)) = 1;
        end
    end
end
% imshow(plate_area);
hori_thresh = sum(plate_area,1);
finx = find(hori_thresh~=0);
hor_start = finx(1);
hor_end = finx(end);
ver_thresh = sum(plate_area,2);
finx = find(ver_thresh~=0);
ver_start = finx(1);
ver_end = finx(end);
plate_region(ver_start:ver_end,hor_start:hor_end) = bw_img(ver_start:ver_end,hor_start:hor_end);
figure;imshow(plate_area);

% Plate extraction...
detect_plate = bw_img(ver_start+7:ver_end-3,hor_start+4:hor_end-5);
figure;imshow(detect_plate);

char_vals = sum(detect_plate,1);

Output

Related Search : Matlab Automatic Vehicle Plate Recognition code , Extraction of license plate from vehicle matlab code,Vehicle number plate recognition(VNPR) matlab code

Matlab read raw file example code , Matlab convert raw file to Jpg example

In below we give the code for convert raw file to Jpg image file example code.In raw file contain slices images . raw format is one of the image compress format.

code :

f=fopen('t1_icbm_normal_1mm_pn3_rf20.rawb');
a=fread(f);
input_img = reshape(a,181,217,181);
[r c m] = size(input_img);

for i = 1 : m
imwrite(input_img(:,:,i),['img_' num2str(i)],'jpg')
figure,imshow(uint8(input_img(:,:,i)));
end

In above code convert raw file to Jpg image file then write the image on current directory and show the each slice images.

Related Search : Matlab read raw file example code , Matlab convert raw file to Jpg example, rawb converter code, Matlab convert rawb to image.

IEEE 14 bus data , IEEE 30 bus data,IEEE 57 bus data for Load flow analysis

In power system, load flow analysis is main process.Here we discus the load flow analysis data's.Like IEEE bus data and line data's.Here below we give one link for Newton-Raphson load-flow analysis technique code. Newton-Raphson technique is compute the load and losses of each bus system.This code contain Standard IEEE data's like bus data and line data.

http://www.mathworks.com/matlabcentral/fileexchange/21059-newton-raphson-loadflow

Download the code and check busdata.m and linedata.m.It contain each bus data and line data.

Keywords : IEEE 14 bus data , IEEE 30 bus data,IEEE 57 bus data for Load flow analysis , Newton-Raphson load-flow code,IEEE 14bus  line data , IEEE 30 bus line data.

Matlab PCA Dimensionality Reduction code,Matlab Toolbox for Dimensionality Reduction

Matlab dimensionality reduction is main process on more research domains.Here we mention some one toolbox for Dimensionality Reduction.This toolbox contain many type of dimensionality reduction techniques are there.

Toolbox home page as below.

http://homepage.tudelft.nl/19j49/Matlab_Toolbox_for_Dimensionality_Reduction.html

Just you download the toolbox.Then add the path of toolbox.click here and check how to set the path for toolboxes.Then compute the dimension reduction on your work.following example for set the path and compute the DR using PCA(Principal Component Analysis)

Code :

>> addpath(genpath('installation_folder/drtoolbox')).

>> mapped_data = compute_mapping(your_data, method, reduction of dimensions, parameters of techniques);

above code to set the path of DM toolbox and calling main function.

Related Search : Matlab PCA Dimensionality Reduction code,Matlab Toolbox for Dimensionality Reduction ,Probabilistic PCA Dimensionality Reduction matlab code,Kernel PCA Dimensionality Reduction matlab code

Matlab Database Connectivity Example code

Databases is collection of structured data .Database actions are data manipulate,data deletion and data insertion. This action we do on Matlab.This action makes use following operational syntax.

1.Create Connection String

Connection String used to connect the database.That syntax as follows

conn_str = database('database_name','username','password','driver','database_url');

Example :

>>conn_str = database('my_db','scott','tiger','oracle.jdbc.driver.OracleDriver','jdbc:oracle:oci7:');

Here we create the connection string on Oracle database.Like you connect different type of  databases.

2.Execute Query String on Database

exec function to execute the query strings on database.Syntax as follows

curs = exec(conn_str, 'sql_query');

Example :

>>curs = exec(conn_str, 'Select * from My_Table');

 above example retrieve the all data's from My_Table.Like you do execute all type of sql queries.

3.Fetch the cursor to a MATLAB variable 

Here we convert the cursor data into matlab variable. example code as below

>>my_data = fetch(curs);

Finally my_data contain all data's of My_Table.

Related Search :  Matlab Database Connectivity Example code, Database connection matlab, Access database connection on matlab, Matlab oracle database connection.