Bit Plane Slicing in MATLAB

       Read fractal.jpg file. Display individual bits as binary image. Display and comment on the result.  (Hint: use bitget built-in function)

CODE:

clc; clear;

A=imread('fractal.jpg');

[row,col]=size(A);

subplot(3,3,1), imshow(A), title('Original Image');

C=zeros(row,col,8);

for k=1:8

    for i=1:row

        for j=1:col

            C(i,j,k)=bitget(A(i,j),k);        %Bit slicing

        end

    end

    subplot(3,3,k+1), imshow(C(:,:,k)), title(['Bit Plane ',num2str(k-1)]);

end

OUTPUT RESULT :

We observe that the three higher order planes, especially the 8^th bit plane, contain a significant amount of the visually significant data. The lower order planes contribute to more subtle intensity details in the image. Decomposing an image into its bit planes is useful for analyzing the relative importance of each bit in the image and is useful for image compression.

How to apply Bounding BOX for selected objects

Connectivity helps in applying bounding box for selected objects.

Calculate  :

i)Area 

ii) Mean 

iii)Centroid 

iv) Perimeter

clear

close all;

I=imread('coins.png');

figure,imshow(I);

B=im2bw(I);

figure,imshow(B);

c=imfill(B,'holes');                            % Fill the holes

figure,imshow(c);

[label,num]=bwlabel(c);

display(num)

object=3;                                       % To apply bounding box for labelled 3

[row,col]=find(label==object); % to find coordinates of the bounding box

sx=min(col)-0.5;

sy=min(row)-0.5;

breadth=max(col)-min(col)+1;

len=max(row)-min(row)+1;

bbox=[sx sy breadth len];

display(bbox);

figure,imshow(I);

hold on;

x=zeros([1 5]);

y=zeros([1 5]);

x(:)=bbox(1);

y(:)=bbox(2);

x(2:3)=bbox(1)+bbox(3);

y(3:4)=bbox(2)+bbox(4);

plot(x,y);

obj_area=numel(row);

display(obj_area);

% Find Centroid

X=mean(col);

Y=mean(row);

Centroid=[X Y];

display(Centroid);

plot(X,Y,'o','color','r');

hold off

%Find perimeter

BW=bwboundaries(label==object);

figure, imshow(I);

hold on

visboundaries(BW);

c=cell2mat(BW(1));

perimeter=0;

for i=1:size(c,1)-1

perimeter=perimeter+sqrt((c(i,1)-c(i+1,1)^2+c(i+1,2)).^2);

end

display(perimeter);

% calculation with regionprops for verification purpose

sdata=regionprops(label,'all'); % click on sdata and check for different parameters

RESULT:

Fig 1

Fig 2