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
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
|
package analyse;
import java.awt.Point;
import java.awt.image.BufferedImage;
import java.awt.image.ColorModel;
import java.awt.image.DataBuffer;
import java.awt.image.DataBufferInt;
import java.awt.image.Raster;
import java.awt.image.SampleModel;
import java.awt.image.renderable.ParameterBlock;
import javax.media.jai.Histogram;
import javax.media.jai.JAI;
import javax.media.jai.PlanarImage;
import javax.media.jai.RasterFactory;
import javax.media.jai.TiledImage;
/**
* Skeleton (v2)
*
* Original algorithm : Dr. Chai Quek
* Modified algorithm : Xavier Philippeau
*
* @author Xavier Philippeau (based on work of Dr. Chai Quek)
*
*/
public class Skeleton {
// Smoothing pattern
private byte[] pattern1={-1,1,0,1,0,0,0,0};
private byte[] pattern2={0,1,0,1,-1,0,0,0};
private byte[] pattern3={0,0,-1,1,0,1,0,0};
private byte[] pattern4={0,0,0,1,0,1,-1,0};
private byte[] pattern5={0,0,0,0,-1,1,0,1};
private byte[] pattern6={-1,0,0,0,0,1,0,1};
private byte[] pattern7={0,1,0,0,0,0,-1,1};
private byte[] pattern8={0,1,-1,0,0,0,0,1};
// Neighbourhood
private int neighbourhood(byte[][] c,int x,int y) {
int neighbourhood=0;
if (c[x-1][y-1]==1) neighbourhood++;
if (c[x-1][y ]==1) neighbourhood++;
if (c[x-1][y+1]==1) neighbourhood++;
if (c[x ][y+1]==1) neighbourhood++;
if (c[x+1][y+1]==1) neighbourhood++;
if (c[x+1][y ]==1) neighbourhood++;
if (c[x+1][y-1]==1) neighbourhood++;
if (c[x ][y-1]==1) neighbourhood++;
return neighbourhood;
}
// Transitions Count
private int transitions(byte[][] c,int x,int y) {
int transitions=0;
if (c[x-1][y-1]==0 && c[x-1][y ]==1) transitions++;
if (c[x-1][y ]==0 && c[x-1][y+1]==1) transitions++;
if (c[x-1][y+1]==0 && c[x ][y+1]==1) transitions++;
if (c[x ][y+1]==0 && c[x+1][y+1]==1) transitions++;
if (c[x+1][y+1]==0 && c[x+1][y ]==1) transitions++;
if (c[x+1][y ]==0 && c[x+1][y-1]==1) transitions++;
if (c[x+1][y-1]==0 && c[x ][y-1]==1) transitions++;
if (c[x ][y-1]==0 && c[x-1][y-1]==1) transitions++;
return transitions;
}
// Match a pattern
private boolean matchPattern(byte[][] c,int x,int y,byte[] pattern) {
if (pattern[0]!=-1 && pattern[0]!=c[x-1][y-1]) return false;
if (pattern[1]!=-1 && pattern[1]!=c[x-1][y ]) return false;
if (pattern[2]!=-1 && pattern[2]!=c[x-1][y+1]) return false;
if (pattern[3]!=-1 && pattern[3]!=c[x ][y+1]) return false;
if (pattern[4]!=-1 && pattern[4]!=c[x+1][y+1]) return false;
if (pattern[5]!=-1 && pattern[5]!=c[x+1][y ]) return false;
if (pattern[6]!=-1 && pattern[6]!=c[x+1][y-1]) return false;
if (pattern[7]!=-1 && pattern[7]!=c[x ][y-1]) return false;
return true;
}
// Match one of the 8 patterns
private boolean matchOneOfPatterns(byte[][] c,int x,int y) {
if (matchPattern(c,x,y,pattern1)) return true;
if (matchPattern(c,x,y,pattern2)) return true;
if (matchPattern(c,x,y,pattern3)) return true;
if (matchPattern(c,x,y,pattern4)) return true;
if (matchPattern(c,x,y,pattern5)) return true;
if (matchPattern(c,x,y,pattern6)) return true;
if (matchPattern(c,x,y,pattern7)) return true;
if (matchPattern(c,x,y,pattern8)) return true;
return false;
}
/**
* Skeletonize the image using succesive thinning.
*
*/
public PlanarImage thinning(PlanarImage imag) {
BufferedImage img= imag.getAsBufferedImage();
int height= img.getHeight();
int width=img.getWidth();
// 3 columns back-buffer (original values)
byte[][]tablo=new byte[width][height];
for(int y=0;y<height;y++){
for(int x=0;x<width;x++){
byte rgb = (byte) img.getRGB(x,y);
if (rgb==-1) tablo[x][y]=1;
else tablo[x][y]=0;
}
}
byte[][] image= tablo;
byte[][] buffer = new byte[3][height];
// initialize the back-buffer
for(int y=0;y<height;y++) {
buffer[0][y]=0;
buffer[1][y]=image[0][y];
buffer[2][y]=image[1][y];
}
// loop until idempotence
for(int loop=0;;loop++) {
boolean changed=false;
// for each columns
for(int x=1;x<(width-1);x++) {
// shift the back-buffer + set the last column
byte[] swp0 = buffer[0]; buffer[0]=buffer[1]; buffer[1]=buffer[2]; buffer[2]=swp0;
for(int y=0;y<height;y++) buffer[2][y]=image[x+1][y];
// for each pixel
for(int y=1;y<(height-1);y++) {
// pixel value
int v = image[x][y];
// pixel not set -> next
if (v==0) continue;
// is a boundary/extremity ?
int currentNeighbourhood = neighbourhood(buffer,1,y);
if (currentNeighbourhood<=1) continue;
if (currentNeighbourhood>=6) continue;
// is a connection ?
int transitionsCount = transitions(image,x,y);
if (transitionsCount==1 && currentNeighbourhood<=3) continue;
// no -> remove this pixel
if (transitionsCount==1) {
changed=true;
image[x][y]=0;
continue;
}
// can we delete this pixel ?
boolean matchOne = matchOneOfPatterns(image,x,y);
// yes -> remove this pixel
if (matchOne) {
changed=true;
image[x][y]=0;
continue;
}
}
}
// no change -> return result
if (!changed) {System.out.println("non"); return imag;}
else {
int[] imageDataSingleArray = new int[width*height];
int count=0;
for(int h=0;h<height;h++)
for(int w=0;w<width;w++){
if (image[w][h]== 1 ) imageDataSingleArray[count++] = 255;
else imageDataSingleArray[count++] = 0;
}
DataBufferInt dbuffer = new DataBufferInt(imageDataSingleArray,width*height);
// Create a byte data sample model.
SampleModel sampleModel =
RasterFactory.createBandedSampleModel(DataBuffer.TYPE_INT,width,height,1);
// Create a compatible ColorModel.
ColorModel colorModel = PlanarImage.createColorModel(sampleModel);
// Create a WritableRaster.
Raster raster = RasterFactory.createWritableRaster(sampleModel,dbuffer,new Point(0,0));
// Create a TiledImage using the SampleModel and ColorModel.
TiledImage tiledImage = new TiledImage(0,0,width,height,0,0,sampleModel,colorModel);
// Set the data of the tiled image to be the raster.
tiledImage.setData(raster);
PlanarImage result = tiledImage;
ParameterBlock pbConvert = new ParameterBlock();
pbConvert.addSource(result);
pbConvert.add(DataBuffer.TYPE_BYTE);
result = JAI.create("format", pbConvert);
System.out.println(result);
return result;
}
}
}
} |
calcul du squelette
Répondre avec citation
Partager