1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
|
package ij.process;
import ij.measure.Calibration;
/** RGB image statistics, including histogram. */
public class ColorStatistics extends ImageStatistics {
/** Construct an ImageStatistics object from a ColorProcessor
using the standard measurement options (area, mean,
mode, min and max). */
public ColorStatistics(ImageProcessor ip) {
this(ip, AREA+MEAN+MODE+MIN_MAX, null);
}
/** Constructs a ColorStatistics object from a ColorProcessor using
the specified measurement options.
*/
public ColorStatistics(ImageProcessor ip, int mOptions, Calibration cal) {
setup(ip, cal);
if (ip instanceof IntProcessor) {
getIntStatistics(ip);
return;
}
ColorProcessor cp = (ColorProcessor)ip;
histogram = cp.getHistogram();
getRawStatistics(0,255);
if ((mOptions&MIN_MAX)!=0)
getRawMinAndMax(0,255);
if ((mOptions&ELLIPSE)!=0 || (mOptions&SHAPE_DESCRIPTORS)!=0)
fitEllipse(ip, mOptions);
else if ((mOptions&CENTROID)!=0)
getCentroid(ip);
if ((mOptions&(CENTER_OF_MASS|SKEWNESS|KURTOSIS))!=0)
calculateMoments(ip);
if ((mOptions&MEDIAN)!=0)
calculateMedian(histogram, 0, 255, cal);
}
void calculateMoments(ImageProcessor ip) {
byte[] mask = ip.getMaskArray();
int i, mi;
double v, v2, sum1=0.0, sum2=0.0, sum3=0.0, sum4=0.0, xsum=0.0, ysum=0.0;
for (int y=ry,my=0; y<(ry+rh); y++,my++) {
i = y*width + rx;
mi = my*rw;
for (int x=rx; x<(rx+rw); x++) {
if (mask==null || mask[mi++]!=0) {
v = ip.getPixelValue(x, y);
v2 = v*v;
sum1 += v;
sum2 += v2;
sum3 += v*v2;
sum4 += v2*v2;
xsum += x*v;
ysum += y*v;
}
i++;
}
}
double mean2 = mean*mean;
double variance = sum2/pixelCount - mean2;
double sDeviation = Math.sqrt(variance);
skewness = ((sum3 - 3.0*mean*sum2)/pixelCount + 2.0*mean*mean2)/(variance*sDeviation);
kurtosis = (((sum4 - 4.0*mean*sum3 + 6.0*mean2*sum2)/pixelCount - 3.0*mean2*mean2)/(variance*variance)-3.0);
xCenterOfMass = xsum/sum1+0.5;
yCenterOfMass = ysum/sum1+0.5;
if (cal!=null) {
xCenterOfMass = cal.getX(xCenterOfMass);
yCenterOfMass = cal.getY(yCenterOfMass, height);
}
}
void getIntStatistics(ImageProcessor ip) {
int v;
int[] pixels = (int[])ip.getPixels();
nBins = ip.getHistogramSize();
histogram = new int[nBins];
double sum = 0;
double sum2 = 0;
byte[] mask = ip.getMaskArray();
// Find image min and max
int roiMin = Integer.MAX_VALUE;
int roiMax = -Integer.MAX_VALUE;
for (int y=ry, my=0; y<(ry+rh); y++, my++) {
int i = y * width + rx;
int mi = my * rw;
for (int x=rx; x<(rx+rw); x++) {
if (mask==null || mask[mi++]!=0) {
v = pixels[i];
if (v<roiMin)
roiMin = v;
if (v>roiMax)
roiMax = v;
}
i++;
}
}
min = roiMin; max = roiMax;
binSize = (max-min)/nBins;
histMin = min;
histMax = max;
// Generate histogram
double scale = nBins/(max-min);
int index;
pixelCount = 0;
for (int y=ry, my=0; y<(ry+rh); y++, my++) {
int i = y * width + rx;
int mi = my * rw;
for (int x=rx; x<(rx+rw); x++) {
if (mask==null || mask[mi++]!=0) {
v = pixels[i];
pixelCount++;
sum += v;
sum2 += v*v;
index = (int)(scale*(v-min));
if (index>=nBins)
index = nBins-1;
histogram[index]++;
}
i++;
}
}
area = pixelCount*pw*ph;
mean = sum/pixelCount;
umean = mean;
calculateStdDev(pixelCount, sum, sum2);
// calculate mode
int count;
maxCount = 0;
for (int i = 0; i < nBins; i++) {
count = histogram[i];
if (count > maxCount) {
maxCount = count;
mode = i;
}
}
dmode = histMin+mode*binSize;
if (binSize!=1.0)
dmode += binSize/2.0;
}
}
|
