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otsuml.pas
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otsuml.pas
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unit otsuml;
//Multilevel Otsu's Method
//Otsu N (1979) A threshold selection method from gray-level histograms. IEEE Trans. Sys., Man., Cyber. 9: 62-66.
//Lookup Tables as suggested by Liao, Chen and Chung (2001) A fast algorithm for multilevel thresholding
//note that my "otsu.pas" is slightly faster and much simpler if you only want bi-level output
interface
uses define_types, sysutils;
function FindOtsu2 (var Img: Bytep; nVox: integer): byte;
//function ApplyOtsu2 (var Img: Bytep; nVox: integer): byte;
//function ApplyOtsu3 (var Img: Bytep; nVox: integer): byte;
//function ApplyOtsu4 (var Img: Bytep; nVox: integer): byte;
procedure ApplyOtsu (var Img: Bytep; nVox, levels: integer);//levels: 2=black/white, 3=3tone, 4=4tone
procedure ApplyOtsuBinary (var Img: Bytep; nVox,levels: integer);
implementation
Type
HistoRAd = array [0..255] of double;
Histo2D = array [0..255] of HistoRAd; //
Function OtsuLUT(var H: HistoRA): Histo2D;
var
Sum,Prob: double;
v,u: integer;//column/rom index
P,S: array of array of double;
//P,S: Histo2D; //<- this works in Lazarus, but crashes Delphi: static arrays are too large for heap
begin
Sum := 0;
for v := 0 to 255 do
Sum := Sum + H[v];
if Sum <= 0 then
exit;
SetLength(P,256,256);
SetLength(S,256,256);
P[0][0] := H[0];
S[0][0] := H[0];
for v := 1 to 255 do begin
prob := H[v]/Sum;
P[0][v] := P[0][v-1]+prob;
S[0][V] := S[0][v-1]+(v+1)*prob;
end;
for u := 1 to 255 do begin
for v := u to 255 do begin
P[u][v] := P[0][v]-P[0][u-1];
S[u][v] := S[0][v]-S[0][u-1];
end
end;
//result is eq 29 from Liao
for u := 0 to 255 do begin
for v := u to 255 do begin
if S[u][v] = 0 then //avoid divide by zero errors...
result[u][v] := 0
else
result[u][v] := sqr(S[u][v]) /P[u][v];
end
end;
P := nil;
S := nil;
end;
(*Function OtsuLUT(var H: HistoRA): Histo2D;
var
Sum,Prob: double;
v,u: integer;//column/rom index
//P,S: Histo2D;
begin
Sum := 0;
for v := 0 to 255 do
Sum := Sum + H[v];
if Sum <= 0 then
exit;
P[0][0] := H[0];
S[0][0] := H[0];
for v := 1 to 255 do begin
prob := H[v]/Sum;
P[0][v] := P[0][v-1]+prob;
S[0][V] := S[0][v-1]+(v+1)*prob;
end;
for u := 1 to 255 do begin
for v := u to 255 do begin
P[u][v] := P[0][v]-P[0][u-1];
S[u][v] := S[0][v]-S[0][u-1];
end
end;
//result is eq 29 from Liao
for u := 0 to 255 do begin
for v := u to 255 do begin
if S[u][v] = 0 then //avoid divide by zero errors...
result[u][v] := 0
else
result[u][v] := sqr(S[u][v]) /P[u][v];
end
end;
end; *)
Function OtsuCostFunc(H: HistoRA): integer;
//Otsu N (1979) A threshold selection method from gray-level histograms". IEEE Trans. Sys., Man., Cyber. 9: 62-66.
//http://en.wikipedia.org/wiki/Otsu's_method
//http://www.labbookpages.co.uk/software/imgProc/otsuThreshold.html
//returns threshold for binarizing an image
// all voxel <=Threshold are background
// all voxel >Threshold are object
const
kMaxBin = 255;
var
t,total: integer;
wB,wF,Sum,SumB,mF,mB,varBetween,varMax: double;
begin
result := 0;
wB := 0;
//wF := 0;
SumB := 0;
Sum := 0;
Total := 0;
varMax := 0;
for t := 0 to kMaxBin do
Total := Total + H[t];
if Total = 0 then exit;
for t := 0 to kMaxBin do
Sum := Sum + (t*H[t]);
for t :=0 to kMaxBin do begin
wB := wB + H[t]; // Weight Background
if (wB = 0) then continue;
wF := Total - wB; // Weight Foreground
if (wF = 0) then break;
sumB := sumB+(t * H[t]);
mB := sumB / wB; // Mean Background
mF := (sum - sumB) / wF; // Mean Foreground
// Calculate Between Class Variance
varBetween := (wB/Total) * (wF/Total) * sqr(mB - mF);
// Check if new maximum found
if (t=0) or (varBetween > varMax) then begin
varMax := varBetween;
result := t;
end;
end;
end;
//OtsuCostFunc2 provides same answer as OtsuCostFunc, but is slightly slower and requires more RAM
function OtsuCostFunc2(lHisto: HistoRA): integer;
var
v,max: double;
h2d: Histo2D;
n: integer;
begin
h2d := OtsuLUT(lHisto);
//default solution
n := 128;
max := h2d[0,n]+h2d[n+1,255];
result := n;
//exhaustively search
for n := 0 to (255-1) do begin
v := h2d[0,n]+h2d[n+1,255];
if v > max then begin
result := n;
max := v;
end; //new max
end; //for n
end; //bilevel OtsuCostFunc2
procedure OtsuCostFunc3(lHisto: HistoRA; var Lo,Hi: integer);
var
v,max: double;
l,h: integer;
h2d: Histo2D;
begin
h2d := OtsuLUT(lHisto);
//default solution
lo := 85;
hi := 170;
max := h2d[0,lo]+h2d[lo+1,Hi]+h2d[Hi+1,255];
//exhaustively search
for l := 0 to (255-2) do begin
for h := l+1 to (255-1) do begin
v := h2d[0,l]+h2d[l+1,h]+h2d[h+1,255];
if v > max then begin
lo := l;
hi := h;
max := v;
end; //new max
end;//for h -> hi
end; //for l -> low
end; //trilevel OtsuCostFunc3
procedure OtsuCostFunc4(var lHisto: HistoRA; var Lo,Mid,Hi: integer);
var
v,max: double;
l,m,h: integer;
h2d: Histo2D;
begin
h2d := OtsuLUT(lHisto);
//default solution
lo := 64;
mid := 128;
hi := 192;
max := h2d[0,lo]+h2d[lo+1,mid]+h2d[mid+1,hi]+h2d[Hi+1,255];
//exhaustively search
for l := 0 to (255-3) do begin
for m := l+1 to (255-2) do begin
for h := m+1 to (255-1) do begin
v := h2d[0,l]+h2d[l+1,m]+h2d[m+1,h]+h2d[h+1,255];
if v > max then begin
lo := l;
mid := m;
hi := h;
max := v;
end; //new max
end;//for h -> hi
end; //for mid
end; //for l -> low
end; //quad OtsuCostFunc4
function FindOtsu2 (var Img: Bytep; nVox: integer): byte;
var
n: integer;
lHisto: HistoRA;
begin
result := 128;
if nVox < 1 then exit;
//create histogram
for n := 0 to 255 do
lHisto[n] := 0;
for n := 1 to nVox do
inc(lHisto[Img^[n]]);
//now find minimum intraclass variance....
//result := OtsuCostFunc(lHisto);
result := OtsuCostFunc2(lHisto); //same answer, just slower and more memory
end;
procedure FindOtsu3 (var Img: Bytep; nVox: integer; var lo, hi: integer);
var
n: integer;
lHisto: HistoRA;
begin
lo := 85;
hi := 170;
if nVox < 1 then exit;
//create histogram
for n := 0 to 255 do
lHisto[n] := 0;
for n := 1 to nVox do
inc(lHisto[Img^[n]]);
//now find minimum intraclass variance....
OtsuCostFunc3(lHisto,lo,hi);
end;
procedure FindOtsu4 (var Img: Bytep; nVox: integer; var lo, med, hi: integer);
var
n: integer;
lHisto: HistoRA;
begin
lo := 64;
med := 128;
hi := 192;
if nVox < 1 then exit;
//create histogram
for n := 0 to 255 do
lHisto[n] := 0;
for n := 1 to nVox do
inc(lHisto[Img^[n]]);
//now find minimum intraclass variance....
OtsuCostFunc4(lHisto,lo,med,hi);
end;
function ApplyOtsu2 (var Img: Bytep; nVox: integer): byte;
var
n: integer;
begin
result := 128;
if nVox < 1 then exit;
result := FindOtsu2(Img,nVox);
for n := 1 to nVox do
if Img^[n] > result then
Img^[n] := 255
else
Img^[n] := 0;
end;
procedure ApplyOtsu3 (var Img: Bytep; nVox: integer);
var
n,lo,hi: integer;
h: histora;
begin
if nVox < 1 then exit;
FindOtsu3(Img,nVox,lo,hi);
for n := 0 to 255 do
if n <= Lo then
H[n] := 0
else if n <= hi then
h[n] := 128
else
h[n] := 255;
for n := 1 to nVox do
Img^[n] := H[Img^[n]];
end;
procedure ApplyOtsu4 (var Img: Bytep; nVox: integer);
var
n,lo,med,hi: integer;
h: histora;
begin
if nVox < 1 then exit;
FindOtsu4(Img,nVox,lo,med,hi);
for n := 0 to 255 do
if n <= Lo then
H[n] := 0
else if n <= med then
h[n] := 85
else if n <= hi then
h[n] := 170
else
h[n] := 255;
for n := 1 to nVox do
Img^[n] := H[Img^[n]];
end;
procedure ApplyOtsu (var Img: Bytep; nVox,levels: integer);
begin
if levels <= 2 then
ApplyOtsu2(Img,nVox)
else if levels = 3 then
ApplyOtsu3(Img,nVox)
else
ApplyOtsu4(Img,nVox);
end;
procedure ApplyOtsuBinary (var Img: Bytep; nVox,levels: integer);
//1=1/4, 2=1/3, 3=1/2, 4=2/3, 5=3/4
var
n: integer;
h: histora;
begin
if nVox < 1 then exit;
if (levels <= 1) or (levels >= 5) then
ApplyOtsu4(Img,nVox)
else if (levels = 2) or (levels = 4) then
ApplyOtsu3(Img,nVox)
else //level = 3
ApplyOtsu2(Img,nVox);
if levels <= 3 then begin //make dark: all except 255 equal 0
for n := 0 to 254 do
H[n] := 0;
H[255] := 255;
end else begin //make bright: all except 0 equal 255
H[0] := 0;
for n := 1 to 255 do
H[n] := 255;
end;
for n := 1 to nVox do
Img^[n] := H[Img^[n]];
end;
end.