I have used the following code from the matlab central website in my project to perform seeded region growing. This works perfectly but I am struggling to understand exactly what the code is doing in some places. I have contacted the author but have had no reply. Would anyone be able to provide me with some explanations ?
function Phi = segCroissRegion(tolerance,Igray,x,y)
if(x == 0 || y == 0)
imshow(Igray,[0 255]);
[x,y] = ginput(1);
end
Phi = false(size(Igray,1),size(Igray,2));
ref = true(size(Igray,1),size(Igray,2));
PhiOld = Phi;
Phi(uint8(x),uint8(y)) = 1;
while(sum(Phi(:)) ~= sum(PhiOld(:)))
PhiOld = Phi;
segm_val = Igray(Phi);
meanSeg = mean(segm_val);
posVoisinsPhi = imdilate(Phi,strel('disk',1,0)) - Phi;
voisins = find(posVoisinsPhi);
valeursVoisins = Igray(voisins);
Phi(voisins(valeursVoisins > meanSeg - tolerance & valeursVoisins < meanSeg + tolerance)) = 1;
end
Thanks
I've added some comments in your code :
function Phi = segCroissRegion(tolerance,Igray,x,y)
% If there's no point, select one from image
if(x == 0 || y == 0)
imshow(Igray,[0 255]);
[x,y] = ginput(1);
end
%Create seed with by adding point in black image
Phi = false(size(Igray,1),size(Igray,2));
ref = true(size(Igray,1),size(Igray,2));
PhiOld = Phi;
Phi(uint8(x),uint8(y)) = 1;
while(sum(Phi(:)) ~= sum(PhiOld(:)))
PhiOld = Phi;
% Evaluate image intensity at seed/line points
segm_val = Igray(Phi);
% Calculate mean intensity at seed/line points
meanSeg = mean(segm_val);
% Grow seed 1 pixel, and remove previous seed (so you'll get only new pixel perimeter)
posVoisinsPhi = imdilate(Phi,strel('disk',1,0)) - Phi;
% Evaluate image intensity over the new perimeter
voisins = find(posVoisinsPhi);
valeursVoisins = Igray(voisins);
% If image intensity over new perimeter is greater than the mean intensity of previous perimeter (minus tolerance), than this perimeter is part of the segmented object
Phi(voisins(valeursVoisins > meanSeg - tolerance & valeursVoisins < meanSeg + tolerance)) = 1;
% Repeat while there's new pixel in seed, stop if no new pixel were added
end
Related
I have a 2D image (matrix). I have found the local maxima of this image. Now I want to define the boundaries around each local maxima in such a way that I want all the pixels around the local maxima that have a value above 85% of the maximum.
Here is my existing code:
function [location]= Mfind_peak_2D( Image,varargin )
p = inputParser;
addParamValue(p,'max_n_loc_max',5);
addParamValue(p,'nb_size',3);
addParamValue(p,'thre',0);
addParamValue(p,'drop',0.15);
parse(p,varargin{:});
p=p.Results;
if sum(isnan(Image(:)))>0
Image(isnan(Image))=0;
end
hLocalMax = vision.LocalMaximaFinder;
hLocalMax.MaximumNumLocalMaxima = p.max_n_loc_max;
hLocalMax.NeighborhoodSize = [p.nb_size p.nb_size];
end
This should do the job (the code is full of comments and should be pretty self-explanatory but if you have doubts feel free to ask for more details):
% Load the image...
img = imread('peppers.png');
img = rgb2gray(img);
% Find the local maxima...
mask = ones(3);
mask(5) = 0;
img_dil = imdilate(img,mask);
lm = img > img_dil;
% Find the neighboring pixels of the local maxima...
img_size = size(img);
img_h = img_size(1);
img_w = img_size(2);
res = cell(sum(sum(lm)),3);
res_off = 1;
for i = 1:img_h
for j = 1:img_w
if (~lm(i,j))
continue;
end
value = img(i,j);
value_thr = value * 0.85;
% Retrieve the neighboring column and row offsets...
c = bsxfun(#plus,j,[-1 0 1 -1 1 -1 0 1]);
r = bsxfun(#plus,i,[-1 -1 -1 0 0 1 1 1]);
% Filter the invalid positions...
idx = (c > 0) & (c <= img_w) & (r > 0) & (r <= img_h);
% Transform the valid positions into linear indices...
idx = (((idx .* c) - 1) .* img_h) + (idx .* r);
idx = reshape(idx.',1,numel(idx));
idx = idx(idx > 0);
% Retrieve the neighbors and filter them based on te threshold...
neighbors = img(idx);
neighbors = neighbors(neighbors > value_thr);
% Update the final result...
res(res_off,:) = {sub2ind(img_size,i,j) value neighbors};
res_off = res_off + 1;
end
end
res = sortrows(res,1);
The variable res will be a cell matrix with three columns: the first one contain the linear indices to the local maxima of the image, the second one contains the values of the local maxima and the third one a vector with the pixels around the local maxima that fall within the specified threshold.
I have written a code to simulate the motion of circular particles in a 2d box. Whenever they move out of the box, I put them inside the box and near the wall. I want to add the diameter (2R) of particles in the code, which means when the distance between the center of two circles become less than 2R, they separate along the line connecting their centers so that the distance between the centers of the circles becomes equal to 2R.
Could anyone suggest a code to perevent the overlapping of particles?
This is my code in which overlap is not considered:
clear all
close all
l = 224; nn = 800; %number of particles
time = 1000; dd = 1;
x= l*rand(1,nn);
y= l*rand(1,nn);
for t = 1:time;
x= x + rand(1,nn)-0.5* ones(1,nn);
y=y+rand(1,nn)-0.5* ones (1,nn);
index = (x < 0); x(index) = abs(normrnd(0,1,1,nnz(index)));
index = (y < 0); y(index) = abs(normrnd(0,1,1,nnz(index)));
index = (x > l); x(index) = l-abs(normrnd(0,1,1,nnz(index)));
index = (y > l); y(index) = l-abs(normrnd(0,1,1,nnz(index)));
end
Here is some commented code which does what you want. Notably:
psize is some defined particle size for interaction.
point-to-point distances found using pdist2.
points that are too close are moved away from each other by some amount (dp times their current distances, if dp=1/2 then their x and y distances double) until there are no clashes.
See comments for details.
clear; close all;
l = 224; nn = 800; % number of particles
time = 100;
x = l*rand(1,nn); y = l*rand(1,nn);
psize = 2; % Particle size for interaction
dp = 0.1;
figure; hold on; axis([0 l 0 l]);
for t = 1:time;
% Random movement
movement = 2*rand(2,nn)-1;
x = x + movement(1,:);
y = y + movement(2,:);
index = (x < 0); x(index) = abs(normrnd(0,1,1,nnz(index)));
index = (y < 0); y(index) = abs(normrnd(0,1,1,nnz(index)));
index = (x > l); x(index) = l-abs(normrnd(0,1,1,nnz(index)));
index = (y > l); y(index) = l-abs(normrnd(0,1,1,nnz(index)));
% Particle interaction. Loop until there are no clashes. For
% robustness, some max iteration counter should be added!
numclash = 1;
while numclash > 0
dists = pdist2([x;y]', [x;y]'); % Distances between all particles
dists(dists < psize) = NaN; % Those too close are assigned NaN
tooclose = isnan(tril(dists,-1)); % All NaNs identified by logical
[clash1,clash2] = find(tooclose); % Get particles which are clashing
numclash = numel(clash1); % Get number of clashes
% All points where there was a clash, move away from each other
x(clash1) = x(clash1) + (x(clash1)-x(clash2))*dp;
x(clash2) = x(clash2) - (x(clash1)-x(clash2))*dp;
y(clash1) = y(clash1) + (y(clash1)-y(clash2))*dp;
y(clash2) = y(clash2) - (y(clash1)-y(clash2))*dp;
end
% Plot to visualise results. Colour fade from dark to bright green over time
scatter(x,y,'.','markeredgecolor',[0.1,t/time,0.4]);
drawnow;
end
hold off
Result:
Edit:
For a clearer diagram, you could initialise some colour matrix C = rand(nn,3); and plot using
scatter(x,y,[],C*(t/time),'.'); % the (t/time) factor makes it fade from dark to light
This would give each particle a different colour, which also fade from dark to light, rather than just fading from dark to light as before. The result would be something like this:
I have a question about changing the color of lines in a plot in MATLAB. I have written a code where I want to change the color of lines in a plot that is embedded in several for loops (the code is shown below). In the code, a new plot is created (with its own figure) when the "if loop" condition is satisfied. I want each plot to have lines with different colors (from other plots), so I created a variable = "NewColor" to increment and change the line colors. However, the following problem has been occurring:
Suppose I am in debug mode and I have stopped at the plot command. I run the next step and a plot is created with a blue line. I check the value of NewColor and find NewColor = 0.1. Next, I use the "run to cursor" command to step to the next time the plot command is activated. When I do this I am still within the "i for loop", so NewColor has not changed. I check the editor to find that NewColor = 0.1. Therefore, when I run the next step a blue line should show up on the current plot. To the contrary and my disbelief an orange line shows up (in addition to the blue line). I don't understand since in both steps of the debugger NewColor = 0.1, and the code is written so the color of the lines = [0,NewColor,0]. If anyone can find the error of my ways it would be greatly appreciated. Thanks
ThetaPlot = [40,50]; % Put incident angle as input
Count1 = 0;
Count2 = 0;
NewColor = 0;
for m = 1:length(ThetaPlot)
NewColor = 0.1;
Title = sprintf('Angle(%d)',ThetaPlot(m));
figure('name',Title)
Count1 = 0;
for i = 1:length(xrange)-1 % X Coordinate of Start Node
for j = 1:length(yrange)-1 % Y Coordinate of Start Node
Count1 = Count1+1;
for k = 2:length(xrange) % X Coordinate of End Node
for l = 2:length(yrange) % Y Coordinate of End Node
Count2 = Count2+1;
if ReflRayData(Count2,ThetaPlot(m) - ThetaIncident(1) + 1,Count1) == 1
x = [xrange(i),xrange(k)];
y = [yrange(j),yrange(l)];
plot(x,y,['-',[0,NewColor,0],'o']);
hold on;
end
end
Count2 = 0;
end
end
end
NewColor = NewColor + 0.02;
end
Full Code:
%% Calculating Angles of Reflection
run = 1; % Set run = 1 for calculations
if run == 1
xrange = [0:1:14.5]'; % Coordinates to try for Panel Geometry (in)
yrange = [0:1:36]'; % Coordinates to try for Panel Geometry (in)
ThetaIncident = [-90:1:90]'; % Incident Angle of Ray (measured relative to normal direction with clockwise postive)
OvenGlassXrange = [14.5:0.1:36.5]; %Range of X coordinates for Oven Glass
ReflRayData = zeros((length(xrange)-1)*(length(yrange)-1),length(ThetaIncident),(length(xrange)-1)*(length(yrange)-1)); % Matrix containing Reflected Ray Data
Count1 = 0;
Count2 = 0;
for i = 1:length(xrange)-1 % X Coordinate of Start Node
for j = 1:length(yrange)-1 % Y Coordinate of Start Node
Count1 = Count1+1;
for k = 2:length(xrange) % X Coordinate of End Node
for l = 2:length(yrange) % Y Coordinate of End Node
Count2 = Count2+1;
for m = 1:length(ThetaIncident)
xStart = xrange(i);
yStart = yrange(j);
xEnd = xrange(k);
yEnd = yrange(l);
m1 = (yEnd - yStart)/(xEnd - xStart); % Slope between Start and End Nodes
b1 = yStart - m1*xStart;
m2 = 1/m1; % Slope of normal direction
b2 = (yEnd - 0.5*(yEnd - yStart)) - m2*(xEnd - 0.5*(xEnd - xStart));
ArbXCoor = 1; % Arbitary Point X Coordinate on Normal Line
ArbYCoor = m2*ArbXCoor+b2; % Arbitary Point Y Coordinate on Normal Line
ThetaReflected = -ThetaIncident(m); % Reflected Angle
ArbXCoorRot = ArbXCoor*cosd(ThetaReflected) - ArbYCoor*sind(ThetaReflected); % Arbitary Point X Coordinate on Reflected Line
ArbYCoorRot = ArbYCoor*cosd(ThetaReflected) + ArbXCoor*sind(ThetaReflected); % Arbitary Point Y Coordinate on Reflected Line
m3 = (ArbYCoorRot - (yEnd - 0.5*(yEnd - yStart)))/(ArbXCoorRot - (xEnd - 0.5*(xEnd - xStart))); % Slope of Reflected Line
b3 = (yEnd - 0.5*(yEnd - yStart)) - m3*(xEnd - 0.5*(xEnd - xStart));
ElemLength = sqrt((yEnd - yStart)^2 + (xEnd - xStart)^2);
if min(OvenGlassXrange) < -b3/m3 && -b3/m3 < max(OvenGlassXrange) && -1 < m1 && m1 < 0 && m1 ~= -Inf && m1 ~= Inf && ElemLength < 3
ReflRayData(Count2,m,Count1) = 1;
end
end
end
end
Count2 = 0;
end
end
%% Plotting
ThetaPlot = [40,50]; % Put incident angle as input
Count1 = 0;
Count2 = 0;
NewColor = 0;
for m = 1:length(ThetaPlot)
NewColor = 0.1;
Title = sprintf('Angle(%d)',ThetaPlot(m));
figure('name',Title)
Count1 = 0;
for i = 1:length(xrange)-1 % X Coordinate of Start Node
for j = 1:length(yrange)-1 % Y Coordinate of Start Node
Count1 = Count1+1;
for k = 2:length(xrange) % X Coordinate of End Node
hold on;
for l = 2:length(yrange) % Y Coordinate of End Node
Count2 = Count2+1;
if ReflRayData(Count2,ThetaPlot(m) - ThetaIncident(1) + 1,Count1) == 1
x = [xrange(i),xrange(k)];
y = [yrange(j),yrange(l)];
plot(x,y,['-',[0,NewColor,0],'o']);
hold on;
end
end
Count2 = 0;
end
end
end
NewColor = NewColor + 0.02;
end
instead of plot(x,y,['-',[0,NewColor,0],'o']); try:
plot(x,y,'linestyle','-','marker','o','color',[0,NewColor,0])
According to the Matlab documentation, by calling hold on Matlab uses the next color.
hold on retains plots in the current axes so that new plots added to the axes do not delete existing plots. New plots use the next colors and line styles based on the ColorOrder and LineStyleOrder properties of the axes.
Therefore, in your code when you call hold on inside the for, it just uses the next color.
My solution is to put figure; hold on; before for loop and remove that one in you loop
Many questions exist already covering how to detect collisions between a line segment and a circle.
In my code, I am using Matlab's linecirc function, then comparing the intersection points it returns with the ends of my line segments, to check that the points are within the line (linecirc assumes an infinite line, which I don't have/want).
Copying and adding some sprintf calls to the linecirc function shows that it is calculating points as intended. These seem to be being lost by my function.
My code is below:
function cutCount = getCutCountHex(R_g, centre)
clf;
cutCount = 0;
% Generate a hex grid
Dg = R_g*2;
L_b = 62;
range = L_b*8;
dx = Dg*cosd(30);
dy = 3*R_g;
xMax = ceil(range/dx); yMax = ceil(range/dy);
d1 = #(xc, yc) [dx*xc dy*yc];
d2 = #(xc, yc) [dx*(xc+0.5) dy*(yc+0.5)];
centres = zeros((xMax*yMax),2);
count = 1;
for yc = 0:yMax-1
for xc = 0:xMax-1
centres(count,:) = d1(xc, yc);
count = count + 1;
centres(count, :) = d2(xc, yc);
count = count + 1;
end
end
for i=1:size(centres,1)
centres(i,:) = centres(i,:) - [xMax/2 * dx, yMax/2 * dy];
end
hold on
axis equal
% Get counter for intersected lines
[VertexX, VertexY] = voronoi(centres(:,1), centres(:,2));
numLines = size(VertexX, 2);
for lc = 1:numLines
segStartPt = [VertexX(1,lc) VertexY(1,lc)];
segEndPt = [VertexX(2,lc) VertexY(2,lc)];
slope = (segEndPt(2) - segStartPt(2))/(segEndPt(1) - segStartPt(1));
intercept = segEndPt(2) - (slope*segEndPt(1));
testSlope = isinf(slope);
if (testSlope(1)==1)
% Pass the x-axis intercept instead
intercept = segStartPt(1);
end
[xInterceptionPoints, yInterceptionPoints] = ...
linecirc(slope, intercept, centre(1), centre(2), L_b);
testArr = isnan(xInterceptionPoints);
if (testArr(1) == 0) % Line intersects. Line segment may not.
interceptionPoint1 = [xInterceptionPoints(1), yInterceptionPoints(1)];
interceptionPoint2 = [xInterceptionPoints(2), yInterceptionPoints(2)];
% Test if first intersection is on the line segment
p1OnSeg = onSeg(segStartPt, segEndPt, interceptionPoint1);
p2OnSeg = onSeg(segStartPt, segEndPt, interceptionPoint2);
if (p1OnSeg == 1)
cutCount = cutCount + 1;
scatter(interceptionPoint1(1), interceptionPoint1(2), 60, 'MarkerFaceColor', 'r', 'MarkerEdgeColor', 'k');
end
% Test if second intersection point is on the line segment
if (interceptionPoint1(1) ~= interceptionPoint2(1) || interceptionPoint1(2) ~= interceptionPoint2(2)) % Don't double count touching points
if (p2OnSeg == 1)
cutCount = cutCount + 1;
scatter(interceptionPoint2(1), interceptionPoint2(2), 60, 'MarkerFaceColor', 'r', 'MarkerEdgeColor', 'k');
end
end
end
end
% Plot circle
viscircles(centre, L_b, 'EdgeColor', 'b');
H = voronoi(centres(:,1), centres(:,2));
for i = 1:size(H)
set(H(i), 'Color', 'g');
end
end
function boolVal = onSeg(segStart, segEnd, testPoint)
bvX = isBetweenOrEq(segStart(1), segEnd(1), testPoint(1));
bvY = isBetweenOrEq(segStart(2), segEnd(2), testPoint(2));
if (bvX == 1 && bvY == 1)
boolVal = 1;
else
boolVal = 0;
end
end
function boolVal = isBetweenOrEq(end1, end2, test)
if ((test <= end1 && test >= end2) || (test >= end1 && test <= end2))
boolVal = 1;
else
boolVal = 0;
end
end
It creates a hexagonal grid, then calculates the number of crossings between a circle drawn with a fixed radius (62 in this case) and a specified centre.
The scatter calls show the locations that the function counts.
Implementing sprintf calls within the if(p1OnSeg == 1) block indicates that my function has chosen fictitious intersection points (although it then deals with them correctly)
if (interceptionPoint1(1) > -26 && interceptionPoint1(1) < -25)
sprintf('p1 = [%f, %f]. Vx = [%f, %f], Vy = [%f, %f].\nxint = [%f, %f], yint = [%f, %f]',...
interceptionPoint1(1), interceptionPoint1(2), VertexX(1,lc), VertexX(2,lc), VertexY(1,lc), VertexY(2,lc),...
xInterceptionPoints(1), xInterceptionPoints(2), yInterceptionPoints(1), yInterceptionPoints(2))
end
Outputs
p1 = [-25.980762, 0.000000]. Vx = [-25.980762, -25.980762], Vy = [-15.000000, 15.000000].
xint = [-25.980762, -25.980762], yint = [0.000000, 0.000000]
A picture shows the strange points.
Sorry for the very long question but - why are these being detected. They don't lie on the circle (displaying values within a mylinecirc function detects the intersections at around (-25, 55) and (-25, -55) or so (as an infinite line would expect).
Moving the circle can remove these points, but sometimes this leads to other problems with detection. What's the deal?
Edit: Rotating my grid pattern created by [Vx, Vy] = voronoi(...) and then removing points with very large values (ie those going close to infinity etc) appears to have fixed this problem. The removal of 'large' value points seems to be necessary to avoid NaN values appearing in 'slope' and 'intercept'. My guess is this is related to a possible slight inclination due to rotation, coupled with then overflow of the expected intercept.
Example code added is below. I also edited in Jan de Gier's code, but that made no difference to the problem and so is not changed in the question code.
%Rotate slightly
RotAngle = 8;
RotMat = [cosd(RotAngle), -sind(RotAngle); sind(RotAngle), cosd(RotAngle)];
for i=1:size(centres,1)
centres(i,:) = centres(i,:) - [floor(xMax/2) * dx, floor(yMax/2) * dy]; %Translation
centres(i,:) = ( RotMat * centres(i,:)' ); %Rotation
end
% Get counter for intersected lines
[VertexX, VertexY] = voronoi(centres(:,1), centres(:,2));
% Filter vertices
numLines = size(VertexX, 2);
newVx = [];
newVy = [];
for lc = 1:numLines
testVec = [VertexX(:,lc) VertexY(:,lc)];
if ~any(abs(testVec) > range*1.5)
newVx = [newVx; VertexX(:,lc)'];
newVy = [newVy; VertexY(:,lc)'];
end
end
VertexX = newVx';
VertexY = newVy';
numLines = size(VertexX, 2);
Still appreciating answers or suggestions to clear up why this is/was occuring.
Example values that cause this are getCutCountHex(30, [0,0]) and ...(35, [0,0])
I cant reproduce your problem, but the thing I did notice is that your onSeg() function might be wrong: it returns true if the testpoint lies in the rectangle with two of the four corner points being segStart and segEnd.
A function that returns true iff a point is on (or more accurate: close enough to) the line segment (segStart,segEnd) could be:
function boolVal = onSeg(segStart, segEnd, testPoint)
tolerance = .5;
AB = sqrt((segEnd(1)-segStart(1))*(segEnd(1)-segStart(1))+(segEnd(2)-segStart(2))*(segEnd(2)-segStart(2)));
AP = sqrt((testPoint(1)-segEnd(1))*(testPoint(1)-segEnd(1))+(testPoint(2)-segEnd(2))*(testPoint(2)-segEnd(2)));
PB = sqrt((segStart(1)-testPoint(1))*(segStart(1)-testPoint(1))+(segStart(2)-testPoint(2))*(segStart(2)-testPoint(2)));
boolVal = abs(AB - (AP + PB)) < tolerance;
end
an approach that I found in one of the anwers here: Find if point lays on line segment. I hope that solves your problem.
I am working on rotating image manually in Matlab. Each time I run my code with a different image the previous images which are rotated are shown in the Figure. I couldn't figure it out. Any help would be appreciable.
The code is here:
[screenshot]
im1 = imread('gradient.jpg');
[h, w, p] = size(im1);
theta = pi/12;
hh = round( h*cos(theta) + w*abs(sin(theta))); %Round to nearest integer
ww = round( w*cos(theta) + h*abs(sin(theta))); %Round to nearest integer
R = [cos(theta) -sin(theta); sin(theta) cos(theta)];
T = [w/2; h/2];
RT = [inv(R) T; 0 0 1];
for z = 1:p
for x = 1:ww
for y = 1:hh
% Using matrix multiplication
i = zeros(3,1);
i = RT*[x-ww/2; y-hh/2; 1];
%% Nearest Neighbour
i = round(i);
if i(1)>0 && i(2)>0 && i(1)<=w && i(2)<=h
im2(y,x,z) = im1(i(2),i(1),z);
end
end
end
end
x=1:ww;
y=1:hh;
[X, Y] = meshgrid(x,y); % Generate X and Y arrays for 3-D plots
orig_pos = [X(:)' ; Y(:)' ; ones(1,numel(X))]; % Number of elements in array or subscripted array expression
orig_pos_2 = [X(:)'-(ww/2) ; Y(:)'-(hh/2) ; ones(1,numel(X))];
new_pos = round(RT*orig_pos_2); % Round to nearest neighbour
% Check if new positions fall from map:
valid_pos = new_pos(1,:)>=1 & new_pos(1,:)<=w & new_pos(2,:)>=1 & new_pos(2,:)<=h;
orig_pos = orig_pos(:,valid_pos);
new_pos = new_pos(:,valid_pos);
siz = size(im1);
siz2 = size(im2);
% Expand the 2D indices to include the third dimension.
ind_orig_pos = sub2ind(siz2,orig_pos(2*ones(p,1),:),orig_pos(ones(p,1),:), (1:p)'*ones(1,length(orig_pos)));
ind_new_pos = sub2ind(siz, new_pos(2*ones(p,1),:), new_pos(ones(p,1),:), (1:p)'*ones(1,length(new_pos)));
im2(ind_orig_pos) = im1(ind_new_pos);
imshow(im2);
There is a problem with the initialization of im2, or rather, the lack of it. im2 is created in the section shown below:
if i(1)>0 && i(2)>0 && i(1)<=w && i(2)<=h
im2(y,x,z) = im1(i(2),i(1),z);
end
If im2 exists before this code is run and its width or height is larger than the image you are generating the new image will only overwrite the top left corner of your existing im2. Try initializing im2 by adding adding
im2 = zeros(hh, ww, p);
before
for z = 1:p
for x = 1:ww
for y = 1:hh
...
As a bonus it might make your code a little faster since Matlab won't have to resize im2 as it grows in the loop.