I am trying to Calculate the CIE Colour Difference DeltaE 2000 based on DE2000 Formula. I have done as per the formula provided in the website, but I am getting strange delta E values. I am confused where I have gone wrong. I have checked manytimes but I am not able to find the mistake.Can someone tell me which part of my code has problem.
function DE_2K = CIEDE2000(Lab1,Lab2)
labuno=Lab1
labdos=Lab2
L1=labuno(1)
a1=labuno(2)
b1=labuno(3)
L2=labdos(1)
a2=labdos(2)
b2=labdos(3)
%*******************************************************************
% Definition for CIE DE2000
%*******************************************************************
L_bar_dash=(L1+L2)/2;
C1 = sqrt((a1)^2+(b1)^2)
C2 = sqrt((a2)^2+(b2)^2)
C_bar = (C1+C2)/2
G = (1 -sqrt(((C_bar)^7)/((C_bar)^7+(25)^7))/2)
a1_dash = a1*(1+G)
a2_dash = a2*(1+G)
C1_dash = sqrt((a1_dash)^2+(b1)^2)
C2_dash = sqrt((a2_dash)^2+(b2)^2)
C_bar_dash = (C1_dash + C2_dash)/2
if (radtodeg(atan(b1/a1_dash)) >= 0 ) h1_dash = radtodeg(atan(b1/a1_dash))
else h1_dash = radtodeg(atan(b1/a1_dash)) + radtodeg(2*pi)
end
if (radtodeg(atan(b2/a2_dash)) >= 0 ) h2_dash = radtodeg(atan(b2/a2_dash))
else h2_dash = radtodeg(atan(b2/a2_dash)) + radtodeg(2*pi)
end
if ((h1_dash - h2_dash) > radtodeg(pi)) H_bar_dash = (h1_dash + h2_dash + radtodeg(2*pi))/2
else H_bar_dash = (h1_dash + h2_dash)/2
end
T = 1 - 0.17*radtodeg(cos(H_bar_dash-radtodeg(pi/6)))+0.24*radtodeg(cos(2*H_bar_dash))+0.32*radtodeg(cos(3*H_bar_dash + radtodeg(pi/30)))- 0.20*radtodeg(cos(4*H_bar_dash + 63))
if ((abs(h2_dash - h1_dash)) <= radtodeg(pi)) DE_h_dash = h2_dash - h1_dash
elseif(abs(h2_dash - h1_dash) > radtodeg(pi) && h2_dash <= h1_dash) DE_h_dash = h2_dash - h1_dash + radtodeg(2*pi)
else DE_h_dash = h2_dash - h1_dash - radtodeg(2*pi)
end
DE_L_dash = L2 - L1
DE_C_dash = C2_dash - C1_dash
DE_H_dash = 2 * sqrt(C1_dash * C2_dash) * radtodeg(sin(DE_h_dash/2))
S_L = 1 + ((0.015 * (L_bar_dash - 50)^2)/sqrt(20 + (L_bar_dash - 50)^2))
S_C = 1 + (0.045 * C_bar_dash)
S_H = 1 + (0.015 * C_bar_dash * T)
DE_angle = 30 * exp( - ((H_bar_dash - 275)/25)^2)
R_C = 2 * sqrt((C_bar_dash)^7/((C_bar_dash)^7 + (25)^7))
R_T = - R_C * radtodeg(sin(2 * DE_angle))
K_L = 1
K_C = 1
K_H = 1
DE_2K = sqrt( (DE_L_dash/(K_L * S_L))^2 + (DE_C_dash/(K_C * S_C))^2 + (DE_H_dash/(K_H * S_H))^2 + (R_T * (DE_C_dash/(K_C * S_C)) * (DE_H_dash/(K_H * S_H))))
end
There are some problems in your calculations:
a) if ((h1_dash - h2_dash) > radtodeg(pi)) : don't you need to take the abs of this?
b) 20*radtodeg(cos(4*H_bar_dash + 63) : you need -63 here
c) I assume your if-else structure correctly handles the three cases; you may need to check that:
....else DE_h_dash = h2_dash - h1_dash - radtodeg(2*pi)
d) sin is a number not in degrees, not in radians so no need to convert here:
radtodeg(sin(DE_h_dash/2))
e) same here: radtodeg(sin(2 * DE_angle))
f) I assume cos/sin take degrees; you many need to double check what is degrees what is radians everywhere.
I need to split trapezoid in 2 part of given size with line, parallel basement. I need to get new h1 of new trapezoid.
For example I have trapezoid of area S and I want to split it in 2 trapezoids of areas S1 and S2.
S1 = aS; S2 = (1-a)S;
S1 = (a+z)*(h1)/2;
S2 = (b+z)*(1-h1)/2;
S1/S2 = KS;
To get new h1 I compare a and b, if a != b, I solve square equation and if a == b I work like with square. But sometimes I get mistakes because of rounding (for example when I solve this analytically I get a = b and program thinks a > b). How can I handle this? Or maybe there is another better way to split trapezoid?
Here is simplifyed code:
if (base > base_prev) {
b_t = base; // base of trapezoid
h = H; //height of trapezoid
a_t = base_prev; //another base of trapezoid
KS = S1 / S2;
a_x = (a_t - b_t) * (1 + KS) / h;
b_x = 2 * KS * b_t + 2 * b_t;
c_x = -(a_t * h + b_t * h);
h_tmp = (-b_x + sqrt(b_x * b_x - 4 * a_x * c_x)) / (2 * a_x);
if (h_tmp > h || h_tmp < 0)
h_tmp = (-b_x - sqrt(b_x * b_x - 4 * a_x * c_x)) / (2 * a_x);
} else if (base < base_prev) {
b_t = base_prev;
a_t = base;
KS = S1 / S2;
a_x = (a_t - b_t) * (1 + KS) / h;
b_x = 2 * KS * b_t + 2 * b_t;
c_x = -(a_t * h + b_t * h);
h_tmp = (-b_x + sqrt(b_x * b_x - 4 * a_x * c_x)) / (2 * a_x);
if (h_tmp > h || h_tmp < 0)
h_tmp = (-b_x - sqrt(b_x * b_x - 4 * a_x * c_x)) / (2 * a_x);
}
else {
KS = S1 / S2;
h_tmp = h * KS;
}
If you're dealing with catastrophic cancellation, one approach, dating back to a classic article by Forsythe, is to use the alternative solution form x = 2c/(-b -+ sqrt(b^2 - 4ac)) for the quadratic equation ax^2 + bx + c = 0. One way to write the two roots, good for b < 0, is
x = (-b + sqrt(b^2 - 4ac))/(2a)
x = 2c/(-b + sqrt(b^2 - 4ac)),
and another, good for b >= 0, is
x = 2c/(-b - sqrt(b^2 - 4ac))
x = (-b - sqrt(b^2 - 4ac))/(2a).
Alternatively, you could use the bisection method to obtain a reasonably good guess and polish it with Newton's method.
I changed the script by adding text instead of an image.
I want to wave was vertically downwards. I know that a little editing but I tried different options and it did not work.
http://jsfiddle.net/7ynn4/3/
var options = {
period:100,
squeeze:0,
wavelength:40,
amplitude:30,
shading:300,
fps:30
}
var ca = document.getElementById('canvas');
var ctx = ca.getContext('2d');
ctx.canvas.width = 400;
ctx.canvas.height = 150;
ctx.font = 'bold 45pt Arial';
ctx.textAlign = 'center';
ctx.fillStyle = 'blue';
ctx.fillText('Hello World', 170, 60);
w = canvas.width,
h = canvas.height,
od = ctx.getImageData( 0, 0, w, h ).data;
setInterval(function() {
var id = ctx.getImageData( 0, 0, w, h ),
d = id.data,
now = ( new Date() )/options.period,
y,
x,
lastO,
shade,
sq = ( y - h/2 ) * options.squeeze,
px,
pct,
o,
y2,
opx;
for ( y = 0; y < h; y += 1 ) {
lastO = 0;
shade = 0;
sq = ( y - h/2 ) * options.squeeze;
for ( x = 0; x < w; x += 1 ) {
px = ( y * w + x ) * 4;
pct = x/w;
o = Math.sin( x/options.wavelength - now ) * options.amplitude * pct;
y2 = y + ( o + sq * pct ) << 0;
opx = ( y2 * w + x ) * 4;
shade = (o-lastO) * options.shading;
d[px ] = od[opx ]+shade;
d[px+1] = od[opx+1]+shade;
d[px+2] = od[opx+2]+shade;
d[px+3] = od[opx+3];
lastO = o;
}
}
ctx.putImageData( id, 0, 0 );
},
1000/options.fps
);
You just flip the values around so that x is affected instead of y -
... vars cut, but replace y2 with x2 ...
/// reversed from here
for (x = 0; x < w; x += 1) {
lastO = 0;
shade = 0;
sq = (x - w * 0.5) * options.squeeze;
for (y = 0; y < h; y += 1) {
px = (y * w + x) * 4;
pct = y / h;
o = Math.sin(y/options.wavelength-now) * options.amplitude * pct;
/// the important one: you might need to compensate here (-5)
x2 = x - 5 + (o + sq * pct) | 0;
opx = (x2 + y * w) * 4;
shade = (o - lastO) * options.shading;
d[px] = od[opx] + shade;
d[px + 1] = od[opx + 1] + shade;
d[px + 2] = od[opx + 2] + shade;
d[px + 3] = od[opx + 3];
lastO = o;
}
}
ctx.putImageData(id, 0, 0);
MODIFIED FIDDLE HERE
I'm using matlab to implement a multilayer neural network. In the code I represent
the value of each node AS netValue{k}
the weight between layer k and k + 1 AS weight{k}
etc.
Since these data is three-dimensional, I have to use cell to hold a 2-D matrix to enable matrix multiply.
So it becomes really really slow to train the model, which I expect to have resulted from the usage of cell.
Can anyone tell me how to accelerate this code? Thanks
clc;
close all;
clear all;
input = [-2 : 0.4 : 2;-2:0.4:2];
ican = 4;
depth = 4; % total layer - 1, by convension
[featureNum , sampleNum] = size(input);
levelNum(1) = featureNum;
levelNum(2) = 5;
levelNum(3) = 5;
levelNum(4) = 5;
levelNum(5) = 2;
weight = cell(0);
for k = 1 : depth
weight{k} = rand(levelNum(k+1), levelNum(k)) - 2 * rand(levelNum(k+1) , levelNum(k));
threshold{k} = rand(levelNum(k+1) , 1) - 2 * rand(levelNum(k+1) , 1);
end
runCount = 0;
sumMSE = 1; % init MSE
minError = 1e-5;
afa = 0.1; % step of "gradient ascendence"
% training loop
while(runCount < 100000 & sumMSE > minError)
sumMSE = 0; % sum of MSE
for i = 1 : sampleNum % sample loop
netValue{1} = input(:,i);
for k = 2 : depth
netValue{k} = weight{k-1} * netValue{k-1} + threshold{k-1}; %calculate each layer
netValue{k} = 1 ./ (1 + exp(-netValue{k})); %apply logistic function
end
netValue{depth+1} = weight{depth} * netValue{depth} + threshold{depth}; %output layer
e = 1 + sin((pi / 4) * ican * netValue{1}) - netValue{depth + 1}; %calc error
assistS{depth} = diag(ones(size(netValue{depth+1})));
s{depth} = -2 * assistS{depth} * e;
for k = depth - 1 : -1 : 1
assistS{k} = diag((1-netValue{k+1}).*netValue{k+1});
s{k} = assistS{k} * weight{k+1}' * s{k+1};
end
for k = 1 : depth
weight{k} = weight{k} - afa * s{k} * netValue{k}';
threshold{k} = threshold{k} - afa * s{k};
end
sumMSE = sumMSE + e' * e;
end
sumMSE = sqrt(sumMSE) / sampleNum;
runCount = runCount + 1;
end
x = [-2 : 0.1 : 2;-2:0.1:2];
y = zeros(size(x));
z = 1 + sin((pi / 4) * ican .* x);
% test
for i = 1 : length(x)
netValue{1} = x(:,i);
for k = 2 : depth
netValue{k} = weight{k-1} * netValue{k-1} + threshold{k-1};
netValue{k} = 1 ./ ( 1 + exp(-netValue{k}));
end
y(:, i) = weight{depth} * netValue{depth} + threshold{depth};
end
plot(x(1,:) , y(1,:) , 'r');
hold on;
plot(x(1,:) , z(1,:) , 'g');
hold off;
Have you used the profiler to find out what functions are actually slowing down your code? It shows what lines take the most time to execute.
I have this program that finds the vanishing point for a given set of images. Is there a way to find the distance from the camera and the vanishing point?
Also once the vanishing point is found out, I manually need to find the X and Y coordinates using the tool provided in matlab. How can i code a snippet that writes all the X and Y coordinates into a text or excel file?
Also is there a better and simpler way to find the vanishing point in matlab?
Matlab Calling Function to find Vanishing Point:
clear all; close all;
dname = 'Height';
files = dir(dname);
files(1) = [];
files(1) = [];
for i=1:size(files, 1)
original = imread(fullfile(dname, files(i).name));
original = imresize(original,0.35);
im = im2double(rgb2gray(original));
[row, col] = findVanishingPoint(im);
imshow(original);hold;plot(col,row,'rx');
saveas(gcf,strcat('Height_Result',num2str(i)),'jpg');
close
end
The findVanishingPoint function:
function [row, col] = findVanishingPoint(im)
DEBUG = 0;
IM = fft2(im);
ROWS = size(IM,1); COLS = size(IM,2);
PERIOD = 2^floor(log2(COLS)-5)+2;
SIZE = floor(10*PERIOD/pi);
SIGMA = SIZE/9;
NORIENT = 72;
E = 8;
[C, S] = createGaborBank(SIZE, PERIOD, SIGMA, NORIENT, ROWS, COLS, E);
D = ones(ROWS, COLS);
AMAX = ifftshift(real(ifft2(C{1}.*IM)).^2+real(ifft2(S{1}.*IM))).^2;
for n=2:NORIENT
A = ifftshift(real(ifft2(C{n}.*IM)).^2+real(ifft2(S{n}.*IM))).^2;
D(find(A > AMAX)) = n;
AMAX = max(A, AMAX);
if (DEBUG==1)
colormap('hot');subplot(131);imagesc(real(A));subplot(132);imagesc(real(AMAX));colorbar;
subplot(133);imagesc(D);
pause
end
end
if (DEBUG==2)
figure('DoubleBuffer','on');
end
T = mean(AMAX(:))-3*std(AMAX(:));
VOTE = zeros(ROWS, COLS);
for row=round(1+SIZE/2):round(ROWS-SIZE/2)
for col=round(1+SIZE/2):round(COLS-SIZE/2)
if (AMAX(row,col) > T)
indices = lineBresenham(ROWS, COLS, col, row, D(row, col)*pi/NORIENT-pi/2);
VOTE(indices) = VOTE(indices)+AMAX(row,col);
end
end
if (DEBUG==2)
colormap('hot');imagesc(VOTE);pause;
end
end
if (DEBUG==2)
close
end
M=1;
[b index] = sort(-VOTE(:));
col = floor((index(1:M)-1) / ROWS)+1;
row = mod(index(1:M)-1, ROWS)+1;
col = round(mean(col));
row = round(mean(row));
The creatGaborBank function:
function [C, S] = createGaborBank(SIZE, PERIOD, SIGMA, NORIENT, ROWS, COLS, E)
if (length(NORIENT)==1)
orientations=[1:NORIENT];
else
orientations = NORIENT;
NORIENT = max(orientations);
end
for n=orientations
[C{n}, S{n}] = gabormask(SIZE, SIGMA, PERIOD, n*pi/NORIENT);
C{n} = fft2(padWithZeros(C{n}, ROWS, COLS));
S{n} = fft2(padWithZeros(S{n}, ROWS, COLS));
end
The gabormask function:
function [cmask, smask] = gabormask(Size, sigma, period, orient, E)
if nargin < 5; E = 8; end;
if nargin < 4; orient = 0; end;
if nargin < 3; period = []; end;
if nargin < 2; sigma = []; end;
if nargin < 1; Size = []; end;
if isempty(period) & isempty(sigma); sigma = 5; end;
if isempty(period); period = sigma*2*sqrt(2); end;
if isempty(sigma); sigma = period/(2*sqrt(2)); end;
if isempty(Size); Size = 2*round(2.575*sigma) + 1; end;
if length(Size) == 1
sx = Size-1; sy = sx;
elseif all(size(Size) == [1 2])
sy = Size(1)-1; sx = Size(2)-1;
else
error('Size must be scalar or 1-by-2 vector');
end;
hy = sy/2; hx = sx/2;
[x, y] = meshgrid(-hx:sx-hx, -hy:sy-hy);
omega = 2*pi/period;
cs = omega * cos(orient);
sn = omega * sin(orient);
k = -1/(E*sigma*sigma);
g = exp(k * (E*x.*x + y.*y));
xp = x * cs + y * sn;
cx = cos(xp);
cmask = g .* cx;
sx = sin(xp);
smask = g .* sx;
cmask = cmask - mean(cmask(:));
cmask = cmask/sum(abs(cmask(:)));
smask = smask - mean(smask(:));
smask = smask/sum(abs(smask(:)));
The padWithZeros function:
function out = padWithZeros(in, ROWS, COLS)
out = padarray(in,[floor((ROWS-size(in,1))/2) floor((COLS-size(in,2))/2)],0,'both');
if size(out,1) == ROWS-1
out = padarray(out,[1 0],0,'pre');
end
if size(out,2) == COLS-1
out = padarray(out,[0 1],0,'pre');
end
The findHorizonEdge function:
function row = findHorizon(im)
DEBUG = 2;
ROWS = size(im,1); COLS = size(im,2);
e = edge(im,'sobel', [], 'horizontal');
dd = sum(e, 2);
N=3;
row = 1;
M = 0;
for i=1+N:length(dd)-N
m = sum(dd(i-N:i+N));
if (m > M)
M = m;
row = i;
end
end
imshow(e);pause
The findHorizon function:
function row = findHorizon(im)
DEBUG = 2;
IM = fft2(im);
ROWS = size(IM,1); COLS = size(IM,2);
PERIOD = 2^floor(log2(COLS)-5)+2;
SIZE = floor(10*PERIOD/pi);
SIGMA = SIZE/9;
NORIENT = 72;
E = 16;
orientations = [NORIENT/2-10:NORIENT/2+10];
[C, S] = createGaborBank(SIZE, PERIOD, SIGMA, orientations, ROWS, COLS, E);
ASUM = zeros(ROWS, COLS);
for n=orientations
A = ifftshift(real(ifft2(C{n}.*IM)).^2+real(ifft2(S{n}.*IM))).^2;
ASUM = ASUM + A;
if (DEBUG==1)
colormap('hot');subplot(131);imagesc(real(A));subplot(132);imagesc(real(AMAX));colorbar;
pause
end
end
ASUM(1:round(1+SIZE/2), :)=0; ASUM(end-round(SIZE/2):end, :)=0;
ASUM(:,end-round(SIZE/2):end)=0; ASUM(:, 1:1+round(SIZE/2))=0;
dd = sum(ASUM, 2);
[temp, row] = sort(-dd);
row = round(mean(row(1:10)));
if (DEBUG == 2)
imagesc(ASUM);hold on;line([1:COLS],repmat(row,COLS));
pause
end
The lineImage function:
function v = lineimage(x0, y0, angle, s)
if (abs(tan(angle)) > 1e015)
a(1,:) = repmat(x0,s(1),1)';
a(2,:) = [1:s(1)];
elseif (abs(tan(angle)) < 1e-015)
a(2,:) = repmat(y0,s(2),1)';
a(1,:) = [1:s(2)];
else
k = tan(angle);
hiX = round((1-(s(1)-y0+1)+k*x0)/k);
loX = round((s(1)-(s(1)-y0+1)+k*x0)/k);
temp = max(loX, hiX);
loX = max(min(loX, hiX), 1);
hiX = min(s(2),temp);
a(1,:) = [loX:hiX];
a(2,:) = max(1, floor(s(1)-(k*a(1,:)+(s(1)-y0+1)-k*x0)));
end
v = (a(1,:)-1).*s(1)+a(2,:);
The lineVector function:
function [abscissa, ordinate] = linevector(x0, y0, angle, s)
if (rad2deg(angle) == 90)
abscissa = repmat(x0,s(1),1);
ordinate = [1:s(1)];
else
k = tan(angle);
hiX = round((1-(s(1)-y0+1)+k*x0)/k);
loX = round((s(1)-(s(1)-y0+1)+k*x0)/k);
temp = max(loX, hiX);
loX = max(min(loX, hiX), 1);
hiX = min(s(2),temp);
abscissa = [loX:hiX];
ordinate = k*abscissa+((s(1)-y0+1)-k*x0);
end
The lineBresenham function:
function [i] = lineBresenham(H,W,Sx,Sy,angle)
k = tan(angle);
if (angle == pi || angle == 0)
Ex = W;
Ey = Sy;
Sx = 1;
elseif (angle == pi/2)
Ey = 1;
i = (Sx-1)*H+[Ey:Sy];
return;
elseif k>0 & k < (Sy-1)/(W-Sx)
Ex = W;
Ey = round(Sy-tan(angle)*(Ex-Sx));
elseif k < 0 & abs(k) < (Sy-1)/(Sx-1)
Ex = 1;
Ey = round(Sy-tan(angle)*(Ex-Sx));
else
Ey = 1;
Ex = round((Sy-1)/tan(angle)+Sx);
end
Dx = Ex - Sx;
Dy = Ey - Sy;
iCoords=1;
if(abs(Dy) <= abs(Dx))
if(Ex >= Sx)
D = 2*Dy + Dx;
IncH = 2*Dy;
IncD = 2*(Dy + Dx);
X = Sx;
Y = Sy;
i(iCoords) = (Sx-1)*H+Sy;
iCoords = iCoords + 1;
while(X < Ex)
if(D >= 0)
D = D + IncH;
X = X + 1;
else
D = D + IncD;
X = X + 1;
Y = Y - 1;
end
i(iCoords) = (X-1)*H+Y;
iCoords = iCoords + 1;
end
else
D = -2*Dy + Dx;
IncH = -2*Dy;
IncD = 2*(-Dy + Dx);
X = Sx;
Y = Sy;
i(iCoords) = (Sx-1)*H+Sy;
iCoords = iCoords + 1;
while(X > Ex)
if(D <= 0)
D = D + IncH;
X = X - 1;
else
D = D + IncD;
X = X - 1;
Y = Y - 1;
end
i(iCoords) = (X-1)*H+Y;
iCoords = iCoords + 1;
end
end
else
Tmp = Ex;
Ex = Ey;
Ey = Tmp;
Tmp = Sx;
Sx = Sy;
Sy = Tmp;
Dx = Ex - Sx;
Dy = Ey - Sy;
if(Ex >= Sx)
D = 2*Dy + Dx;
IncH = 2*Dy;
IncD = 2*(Dy + Dx);
X = Sx;
Y = Sy;
i(iCoords) = (Sy-1)*H+Sx;
iCoords = iCoords + 1;
while(X < Ex)
if(D >= 0)
D = D + IncH;
X = X + 1;
else
D = D + IncD;
X = X + 1;
Y = Y - 1;
end
i(iCoords) = (Y-1)*H+X;
iCoords = iCoords + 1;
end
else
D = -2*Dy + Dx;
IncH = -2*Dy;
IncD = 2*(-Dy + Dx);
X = Sx;
Y = Sy;
i(iCoords) = (Sy-1)*H+Sx;
iCoords = iCoords + 1;
while(X > Ex)
if(D <= 0)
D = D + IncH;
X = X - 1;
else
D = D + IncD;
X = X - 1;
Y = Y - 1;
end
i(iCoords) = (Y-1)*H+X;
iCoords = iCoords + 1;
end
end
end
The vanishing point is at infinity hence the distance to the camera is of no use.
Use xlswrite or dlmwrite to write into excel or text file respectively.