验证码图片

验证码图片

http://www.oschina.net/code/snippet_616487_15391 原网址:

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
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
package
com.coolinsoft.miaosha.util.ocr;
 
import
java.awt.Color;
import
java.awt.Graphics2D;
import
java.awt.color.ColorSpace;
import
java.awt.geom.AffineTransform;
import
java.awt.image.AffineTransformOp;
import
java.awt.image.BufferedImage;
import
java.awt.image.ColorConvertOp;
import
java.awt.image.ColorModel;
import
java.awt.image.MemoryImageSource;
import
java.awt.image.PixelGrabber;
import
java.util.HashMap;
import
java.util.Map;
 
public
class
ImageFilter {
    
private
BufferedImage image;
    
private
int
iw, ih;  
//图片宽度、高度
    
private
int
[] pixels;
//像素
 
    
public
ImageFilter(BufferedImage image) {
        
this
.image = image;
        
iw = image.getWidth();
        
ih = image.getHeight();
        
pixels =
new
int
[iw * ih];
    
}
 
    
/** 图像二值化 */
    
public
BufferedImage changeGrey() {
        
PixelGrabber pg =
new
PixelGrabber(image.getSource(),
0
,
0
, iw, ih,pixels,
0
, iw);
        
try
{
            
pg.grabPixels();
        
}
catch
(InterruptedException e) {
            
e.printStackTrace();
        
}
        
// 设定二值化的域值,默认值为100
        
int
grey =
150
;
        
// 对图像进行二值化处理,Alpha值保持不变
        
ColorModel cm = ColorModel.getRGBdefault();
        
for
(
int
i =
0
; i < iw * ih; i++) {
            
int
red, green, blue;
            
int
alpha = cm.getAlpha(pixels[i]);
            
if
(cm.getRed(pixels[i]) > grey) {
                
red =
255
;
            
}
else
{
                
red =
0
;
            
}
 
            
if
(cm.getGreen(pixels[i]) > grey) {
                
green =
255
;
            
}
else
{
                
green =
0
;
            
}
 
            
if
(cm.getBlue(pixels[i]) > grey) {
                
blue =
255
;
            
}
else
{
                
blue =
0
;
            
}
 
            
pixels[i] = alpha <<
24
| red <<
16
| green <<
8
| blue;
        
}
        
// 将数组中的象素产生一个图像
        
return
ImageIOHelper.imageProducerToBufferedImage(
new
MemoryImageSource(iw, ih,pixels,
0
, iw));
    
}
 
    
/** 提升清晰度,进行锐化 */
    
public
BufferedImage sharp() {
        
PixelGrabber pg =
new
PixelGrabber(image.getSource(),
0
,
0
, iw, ih,
                
pixels,
0
, iw);
        
try
{
            
pg.grabPixels();
        
}
catch
(InterruptedException e) {
            
e.printStackTrace();
        
}
 
        
// 象素的中间变量
        
int
tempPixels[] =
new
int
[iw * ih];
        
for
(
int
i =
0
; i < iw * ih; i++) {
            
tempPixels[i] = pixels[i];
        
}
        
// 对图像进行尖锐化处理,Alpha值保持不变
        
ColorModel cm = ColorModel.getRGBdefault();
        
for
(
int
i =
1
; i < ih -
1
; i++) {
            
for
(
int
j =
1
; j < iw -
1
; j++) {
                
int
alpha = cm.getAlpha(pixels[i * iw + j]);
 
                
// 对图像进行尖锐化
                
int
red6 = cm.getRed(pixels[i * iw + j +
1
]);
                
int
red5 = cm.getRed(pixels[i * iw + j]);
                
int
red8 = cm.getRed(pixels[(i +
1
) * iw + j]);
                
int
sharpRed = Math.abs(red6 - red5) + Math.abs(red8 - red5);
 
                
int
green5 = cm.getGreen(pixels[i * iw + j]);
                
int
green6 = cm.getGreen(pixels[i * iw + j +
1
]);
                
int
green8 = cm.getGreen(pixels[(i +
1
) * iw + j]);
                
int
sharpGreen = Math.abs(green6 - green5)
                        
+ Math.abs(green8 - green5);
 
                
int
blue5 = cm.getBlue(pixels[i * iw + j]);
                
int
blue6 = cm.getBlue(pixels[i * iw + j +
1
]);
                
int
blue8 = cm.getBlue(pixels[(i +
1
) * iw + j]);
                
int
sharpBlue = Math.abs(blue6 - blue5)
                        
+ Math.abs(blue8 - blue5);
 
                
if
(sharpRed >
255
) {
                    
sharpRed =
255
;
                
}
                
if
(sharpGreen >
255
) {
                    
sharpGreen =
255
;
                
}
                
if
(sharpBlue >
255
) {
                    
sharpBlue =
255
;
                
}
 
                
tempPixels[i * iw + j] = alpha <<
24
| sharpRed <<
16
                        
| sharpGreen <<
8
| sharpBlue;
            
}
        
}
 
        
// 将数组中的象素产生一个图像
        
return
ImageIOHelper
                
.imageProducerToBufferedImage(
new
MemoryImageSource(iw, ih,
                        
tempPixels,
0
, iw));
    
}
     
     
     
     
     
     
 
 
    
public
static
int
isWhite(
int
colorInt) {
        
Color color =
new
Color(colorInt);
        
if
(color.getRed() + color.getGreen() + color.getBlue() >
600
) {
            
return
1
;
        
}
        
return
0
;
    
}
     
    
public 
BufferedImage removeBackgroud(){
        
BufferedImage img =
this
.image;
        
img = img.getSubimage(
1
,
1
, img.getWidth() -
2
, img.getHeight() -
2
);
        
int
width = img.getWidth();
        
int
height = img.getHeight();
        
double
subWidth = (
double
) width /
5.0
;
        
for
(
int
i =
0
; i <
5
; i++) {
            
Map<Integer, Integer> map =
new
HashMap<Integer, Integer>();
           
for
(
int
x = (
int
) (
1
+ i * subWidth); x < (i +
1
) * subWidth && x < width -
1
; ++x) {
              
for
(
int
y =
0
; y < height; ++y) {
                  
if
(isWhite(img.getRGB(x, y)) ==
1
)
                      
continue
;
                  
if
(map.containsKey(img.getRGB(x, y))) {
                      
map.put(img.getRGB(x, y), map.get(img.getRGB(x, y)) +
1
);
                  
}
else
{
                      
map.put(img.getRGB(x, y),
1
);
                  
}
              
}
           
}
           
int
max =
0
;
           
int
colorMax =
0
;
           
for
(Integer color : map.keySet()) {
                
if
(max < map.get(color)) {
                 
max = map.get(color);
                 
colorMax = color;
           
}
        
}
        
for
(
int
x = (
int
) (
1
+ i * subWidth); x < (i +
1
) * subWidth && x < width -
1
; ++x) {
            
for
(
int
y =
0
; y < height; ++y) {
                
if
(img.getRGB(x, y) != colorMax) {
                    
img.setRGB(x, y, Color.WHITE.getRGB());
                
}
else
{
                     
img.setRGB(x, y, Color.BLACK.getRGB());
                
}
            
}
        
}
      
}
       
return
img;
   
}
     
 
    
/** 中值滤波 */
    
public
BufferedImage median() {
        
PixelGrabber pg =
new
PixelGrabber(image.getSource(),
0
,
0
, iw, ih,
                
pixels,
0
, iw);
        
try
{
            
pg.grabPixels();
        
}
catch
(InterruptedException e) {
            
e.printStackTrace();
        
}
        
// 对图像进行中值滤波,Alpha值保持不变
        
ColorModel cm = ColorModel.getRGBdefault();
        
for
(
int
i =
1
; i < ih -
1
; i++) {
            
for
(
int
j =
1
; j < iw -
1
; j++) {
                
int
red, green, blue;
                
int
alpha = cm.getAlpha(pixels[i * iw + j]);
 
                
//int red2 = cm.getRed(pixels[(i - 1) * iw + j]);
                
int
red4 = cm.getRed(pixels[i * iw + j -
1
]);
                
int
red5 = cm.getRed(pixels[i * iw + j]);
                
int
red6 = cm.getRed(pixels[i * iw + j +
1
]);
                
//int red8 = cm.getRed(pixels[(i + 1) * iw + j]);
 
                
// 水平方向进行中值滤波
                
if
(red4 >= red5) {
                    
if
(red5 >= red6) {
                        
red = red5;
                    
}
else
{
                        
if
(red4 >= red6) {
                            
red = red6;
                        
}
else
{
                            
red = red4;
                        
}
                    
}
                
}
else
{
                    
if
(red4 > red6) {
                        
red = red4;
                    
}
else
{
                        
if
(red5 > red6) {
                            
red = red6;
                        
}
else
{
                            
red = red5;
                        
}
                    
}
                
}
 
                
// int green2 = cm.getGreen(pixels[(i - 1) * iw + j]);
                
int
green4 = cm.getGreen(pixels[i * iw + j -
1
]);
                
int
green5 = cm.getGreen(pixels[i * iw + j]);
                
int
green6 = cm.getGreen(pixels[i * iw + j +
1
]);
                
// int green8 = cm.getGreen(pixels[(i + 1) * iw + j]);
 
                
// 水平方向进行中值滤波
                
if
(green4 >= green5) {
                    
if
(green5 >= green6) {
                        
green = green5;
                    
}
else
{
                        
if
(green4 >= green6) {
                            
green = green6;
                        
}
else
{
                            
green = green4;
                        
}
                    
}
                
}
else
{
                    
if
(green4 > green6) {
                        
green = green4;
                    
}
else
{
                        
if
(green5 > green6) {
                            
green = green6;
                        
}
else
{
                            
green = green5;
                        
}
                    
}
                
}
 
                
// int blue2 = cm.getBlue(pixels[(i - 1) * iw + j]);
                
int
blue4 = cm.getBlue(pixels[i * iw + j -
1
]);
                
int
blue5 = cm.getBlue(pixels[i * iw + j]);
                
int
blue6 = cm.getBlue(pixels[i * iw + j +
1
]);
                
// int blue8 = cm.getBlue(pixels[(i + 1) * iw + j]);
 
                
// 水平方向进行中值滤波
                
if
(blue4 >= blue5) {
                    
if
(blue5 >= blue6) {
                        
blue = blue5;
                    
}
else
{
                        
if
(blue4 >= blue6) {
                            
blue = blue6;
                        
}
else
{
                            
blue = blue4;
                        
}
                    
}
                
}
else
{
                    
if
(blue4 > blue6) {
                        
blue = blue4;
                    
}
else
{
                        
if
(blue5 > blue6) {
                            
blue = blue6;
                        
}
else
{
                            
blue = blue5;
                        
}
                    
}
                
}
                
pixels[i * iw + j] = alpha <<
24
| red <<
16
| green <<
8
                        
| blue;
            
}
        
}
 
        
// 将数组中的象素产生一个图像
        
return
ImageIOHelper
                
.imageProducerToBufferedImage(
new
MemoryImageSource(iw, ih,
                        
pixels,
0
, iw));
    
}
 
    
/** 线性灰度变换 */
    
public
BufferedImage lineGrey() {
        
PixelGrabber pg =
new
PixelGrabber(image.getSource(),
0
,
0
, iw, ih,
                
pixels,
0
, iw);
        
try
{
            
pg.grabPixels();
        
}
catch
(InterruptedException e) {
            
e.printStackTrace();
        
}
        
// 对图像进行进行线性拉伸,Alpha值保持不变
        
ColorModel cm = ColorModel.getRGBdefault();
        
for
(
int
i =
0
; i < iw * ih; i++) {
            
int
alpha = cm.getAlpha(pixels[i]);
            
int
red = cm.getRed(pixels[i]);
            
int
green = cm.getGreen(pixels[i]);
            
int
blue = cm.getBlue(pixels[i]);
 
            
// 增加了图像的亮度
            
red = (
int
) (
1.1
* red +
30
);
            
green = (
int
) (
1.1
* green +
30
);
            
blue = (
int
) (
1.1
* blue +
30
);
            
if
(red >=
255
) {
                
red =
255
;
            
}
            
if
(green >=
255
) {
                
green =
255
;
            
}
            
if
(blue >=
255
) {
                
blue =
255
;
            
}
            
pixels[i] = alpha <<
24
| red <<
16
| green <<
8
| blue;
        
}
 
        
// 将数组中的象素产生一个图像
 
        
return
ImageIOHelper
                
.imageProducerToBufferedImage(
new
MemoryImageSource(iw, ih,
                        
pixels,
0
, iw));
    
}
 
    
/** 转换为黑白灰度图 */
    
public
BufferedImage grayFilter() {
        
ColorSpace cs = ColorSpace.getInstance(ColorSpace.CS_GRAY);
        
ColorConvertOp op =
new
ColorConvertOp(cs,
null
);
        
return
op.filter(image,
null
);
    
}
 
    
/** 平滑缩放 */
    
public
BufferedImage scaling(
double
s) {
        
AffineTransform tx =
new
AffineTransform();
        
tx.scale(s, s);
        
AffineTransformOp op =
new
AffineTransformOp(tx,
                
AffineTransformOp.TYPE_BILINEAR);
        
return
op.filter(image,
null
);
    
}
 
    
public
BufferedImage scale(Float s) {
        
int
srcW = image.getWidth();
        
int
srcH = image.getHeight();
        
int
newW = Math.round(srcW * s);
        
int
newH = Math.round(srcH * s);
        
// 先做水平方向上的伸缩变换
        
BufferedImage tmp =
new
BufferedImage(newW, newH, image.getType());
        
Graphics2D g = tmp.createGraphics();
        
for
(
int
x =
0
; x < newW; x++) {
            
g.setClip(x,
0
,
1
, srcH);
            
// 按比例放缩
            
g.drawImage(image, x - x * srcW / newW,
0
,
null
);
        
}
 
        
// 再做垂直方向上的伸缩变换
        
BufferedImage dst =
new
BufferedImage(newW, newH, image.getType());
        
g = dst.createGraphics();
        
for
(
int
y =
0
; y < newH; y++) {
            
g.setClip(
0
, y, newW,
1
);
            
// 按比例放缩
            
g.drawImage(tmp,
0
, y - y * srcH / newH,
null
);
        
}
        
return
dst;
    
}
 
}

代码]将验证码抽取下来之后 零食存在本地 惊进行解析     跳至 [1] [全屏预览]

?
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
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
package
com.coolinsoft.miaosha.util.ocr;
 
import
java.awt.Color;
import
java.awt.Graphics2D;
import
java.awt.color.ColorSpace;
import
java.awt.geom.AffineTransform;
import
java.awt.image.AffineTransformOp;
import
java.awt.image.BufferedImage;
import
java.awt.image.ColorConvertOp;
import
java.awt.image.ColorModel;
import
java.awt.image.MemoryImageSource;
import
java.awt.image.PixelGrabber;
import
java.util.HashMap;
import
java.util.Map;
 
public
class
ImageFilter {
    
private
BufferedImage image;
    
private
int
iw, ih;  
//图片宽度、高度
    
private
int
[] pixels;
//像素
 
    
public
ImageFilter(BufferedImage image) {
        
this
.image = image;
        
iw = image.getWidth();
        
ih = image.getHeight();
        
pixels =
new
int
[iw * ih];
    
}
 
    
/** 图像二值化 */
    
public
BufferedImage changeGrey() {
        
PixelGrabber pg =
new
PixelGrabber(image.getSource(),
0
,
0
, iw, ih,pixels,
0
, iw);
        
try
{
            
pg.grabPixels();
        
}
catch
(InterruptedException e) {
            
e.printStackTrace();
        
}
        
// 设定二值化的域值,默认值为100
        
int
grey =
150
;
        
// 对图像进行二值化处理,Alpha值保持不变
        
ColorModel cm = ColorModel.getRGBdefault();
        
for
(
int
i =
0
; i < iw * ih; i++) {
            
int
red, green, blue;
            
int
alpha = cm.getAlpha(pixels[i]);
            
if
(cm.getRed(pixels[i]) > grey) {
                
red =
255
;
            
}
else
{
                
red =
0
;
            
}
 
            
if
(cm.getGreen(pixels[i]) > grey) {
                
green =
255
;
            
}
else
{
                
green =
0
;
            
}
 
            
if
(cm.getBlue(pixels[i]) > grey) {
                
blue =
255
;
            
}
else
{
                
blue =
0
;
            
}
 
            
pixels[i] = alpha <<
24
| red <<
16
| green <<
8
| blue;
        
}
        
// 将数组中的象素产生一个图像
        
return
ImageIOHelper.imageProducerToBufferedImage(
new
MemoryImageSource(iw, ih,pixels,
0
, iw));
    
}
 
    
/** 提升清晰度,进行锐化 */
    
public
BufferedImage sharp() {
        
PixelGrabber pg =
new
PixelGrabber(image.getSource(),
0
,
0
, iw, ih,
                
pixels,
0
, iw);
        
try
{
            
pg.grabPixels();
        
}
catch
(InterruptedException e) {
            
e.printStackTrace();
        
}
 
        
// 象素的中间变量
        
int
tempPixels[] =
new
int
[iw * ih];
        
for
(
int
i =
0
; i < iw * ih; i++) {
            
tempPixels[i] = pixels[i];
        
}
        
// 对图像进行尖锐化处理,Alpha值保持不变
        
ColorModel cm = ColorModel.getRGBdefault();
        
for
(
int
i =
1
; i < ih -
1
; i++) {
            
for
(
int
j =
1
; j < iw -
1
; j++) {
                
int
alpha = cm.getAlpha(pixels[i * iw + j]);
 
                
// 对图像进行尖锐化
                
int
red6 = cm.getRed(pixels[i * iw + j +
1
]);
                
int
red5 = cm.getRed(pixels[i * iw + j]);
                
int
red8 = cm.getRed(pixels[(i +
1
) * iw + j]);
                
int
sharpRed = Math.abs(red6 - red5) + Math.abs(red8 - red5);
 
                
int
green5 = cm.getGreen(pixels[i * iw + j]);
                
int
green6 = cm.getGreen(pixels[i * iw + j +
1
]);
                
int
green8 = cm.getGreen(pixels[(i +
1
) * iw + j]);
                
int
sharpGreen = Math.abs(green6 - green5)
                        
+ Math.abs(green8 - green5);
 
                
int
blue5 = cm.getBlue(pixels[i * iw + j]);
                
int
blue6 = cm.getBlue(pixels[i * iw + j +
1
]);
                
int
blue8 = cm.getBlue(pixels[(i +
1
) * iw + j]);
                
int
sharpBlue = Math.abs(blue6 - blue5)
                        
+ Math.abs(blue8 - blue5);
 
                
if
(sharpRed >
255
) {
                    
sharpRed =
255
;
                
}
                
if
(sharpGreen >
255
) {
                    
sharpGreen =
255
;
                
}
                
if
(sharpBlue >
255
) {
                    
sharpBlue =
255
;
                
}
 
                
tempPixels[i * iw + j] = alpha <<
24
| sharpRed <<
16
                        
| sharpGreen <<
8
| sharpBlue;
            
}
        
}
 
        
// 将数组中的象素产生一个图像
        
return
ImageIOHelper
                
.imageProducerToBufferedImage(
new
MemoryImageSource(iw, ih,
                        
tempPixels,
0
, iw));
    
}
     
     
     
     
     
     
 
 
    
public
static
int
isWhite(
int
colorInt) {
        
Color color =
new
Color(colorInt);
        
if
(color.getRed() + color.getGreen() + color.getBlue() >
600
) {
            
return
1
;
        
}
        
return
0
;
    
}
     
    
public 
BufferedImage removeBackgroud(){
        
BufferedImage img =
this
.image;
        
img = img.getSubimage(
1
,
1
, img.getWidth() -
2
, img.getHeight() -
2
);
        
int
width = img.getWidth();
        
int
height = img.getHeight();
        
double
subWidth = (
double
) width /
5.0
;
        
for
(
int
i =
0
; i <
5
; i++) {
            
Map<Integer, Integer> map =
new
HashMap<Integer, Integer>();
           
for
(
int
x = (
int
) (
1
+ i * subWidth); x < (i +
1
) * subWidth && x < width -
1
; ++x) {
              
for
(
int
y =
0
; y < height; ++y) {
                  
if
(isWhite(img.getRGB(x, y)) ==
1
)
                      
continue
;
                  
if
(map.containsKey(img.getRGB(x, y))) {
                      
map.put(img.getRGB(x, y), map.get(img.getRGB(x, y)) +
1
);
                  
}
else
{
                      
map.put(img.getRGB(x, y),
1
);
                  
}
              
}
           
}
           
int
max =
0
;
           
int
colorMax =
0
;
           
for
(Integer color : map.keySet()) {
                
if
(max < map.get(color)) {
                 
max = map.get(color);
                 
colorMax = color;
           
}
        
}
        
for
(
int
x = (
int
) (
1
+ i * subWidth); x < (i +
1
) * subWidth && x < width -
1
; ++x) {
            
for
(
int
y =
0
; y < height; ++y) {
                
if
(img.getRGB(x, y) != colorMax) {
                    
img.setRGB(x, y, Color.WHITE.getRGB());
                
}
else
{
                     
img.setRGB(x, y, Color.BLACK.getRGB());
                
}
            
}
        
}
      
}
       
return
img;
   
}
     
 
    
/** 中值滤波 */
    
public
BufferedImage median() {
        
PixelGrabber pg =
new
PixelGrabber(image.getSource(),
0
,
0
, iw, ih,
                
pixels,
0
, iw);
        
try
{
            
pg.grabPixels();
        
}
catch
(InterruptedException e) {
            
e.printStackTrace();
        
}
        
// 对图像进行中值滤波,Alpha值保持不变
        
ColorModel cm = ColorModel.getRGBdefault();
        
for
(
int
i =
1
; i < ih -
1
; i++) {
            
for
(
int
j =
1
; j < iw -
1
; j++) {
                
int
red, green, blue;
                
int
alpha = cm.getAlpha(pixels[i * iw + j]);
 
                
//int red2 = cm.getRed(pixels[(i - 1) * iw + j]);
                
int
red4 = cm.getRed(pixels[i * iw + j -
1
]);
                
int
red5 = cm.getRed(pixels[i * iw + j]);
                
int
red6 = cm.getRed(pixels[i * iw + j +
1
]);
                
//int red8 = cm.getRed(pixels[(i + 1) * iw + j]);
 
                
// 水平方向进行中值滤波
                
if
(red4 >= red5) {
                    
if
(red5 >= red6) {
                        
red = red5;
                    
}
else
{
                        
if
(red4 >= red6) {
                            
red = red6;
                        
}
else
{
                            
red = red4;
                        
}
                    
}
                
}
else
{
                    
if
(red4 > red6) {
                        
red = red4;
                    
}
else
{
                        
if
(red5 > red6) {
                            
red = red6;
                        
}
else
{
                            
red = red5;
                        
}
                    
}
                
}
 
                
// int green2 = cm.getGreen(pixels[(i - 1) * iw + j]);
                
int
green4 = cm.getGreen(pixels[i * iw + j -
1
]);
                
int
green5 = cm.getGreen(pixels[i * iw + j]);
                
int
green6 = cm.getGreen(pixels[i * iw + j +
1
]);
                
// int green8 = cm.getGreen(pixels[(i + 1) * iw + j]);
 
                
// 水平方向进行中值滤波
                
if
(green4 >= green5) {
                    
if
(green5 >= green6) {
                        
green = green5;
                    
}
else
{
                        
if
(green4 >= green6) {
                            
green = green6;
                        
}
else
{
                            
green = green4;
                        
}
                    
}
                
}
else
{
                    
if
(green4 > green6) {
                        
green = green4;
                    
}
else
{
                        
if
(green5 > green6) {
                            
green = green6;
                        
}
else
{
                            
green = green5;
                        
}
                    
}
                
}
 
                
// int blue2 = cm.getBlue(pixels[(i - 1) * iw + j]);
                
int
blue4 = cm.getBlue(pixels[i * iw + j -
1
]);
                
int
blue5 = cm.getBlue(pixels[i * iw + j]);
                
int
blue6 = cm.getBlue(pixels[i * iw + j +
1
]);
                
// int blue8 = cm.getBlue(pixels[(i + 1) * iw + j]);
 
                
// 水平方向进行中值滤波
                
if
(blue4 >= blue5) {
                    
if
(blue5 >= blue6) {
                        
blue = blue5;
                    
}
else
{
                        
if
(blue4 >= blue6) {
                            
blue = blue6;
                        
}
else
{
                            
blue = blue4;
                        
}
                    
}
                
}
else
{
                    
if
(blue4 > blue6) {
                        
blue = blue4;
                    
}
else
{
                        
if
(blue5 > blue6) {
                            
blue = blue6;
                        
}
else
{
                            
blue = blue5;
                        
}
                    
}
                
}
                
pixels[i * iw + j] = alpha <<
24
| red <<
16
| green <<
8
                        
| blue;
            
}
        
}
 
        
// 将数组中的象素产生一个图像
        
return
ImageIOHelper
                
.imageProducerToBufferedImage(
new
MemoryImageSource(iw, ih,
                        
pixels,
0
, iw));
    
}
 
    
/** 线性灰度变换 */
    
public
BufferedImage lineGrey() {
        
PixelGrabber pg =
new
PixelGrabber(image.getSource(),
0
,
0
, iw, ih,
                
pixels,
0
, iw);
        
try
{
            
pg.grabPixels();
        
}
catch
(InterruptedException e) {
            
e.printStackTrace();
        
}
        
// 对图像进行进行线性拉伸,Alpha值保持不变
        
ColorModel cm = ColorModel.getRGBdefault();
        
for
(
int
i =
0
; i < iw * ih; i++) {
            
int
alpha = cm.getAlpha(pixels[i]);
            
int
red = cm.getRed(pixels[i]);
            
int
green = cm.getGreen(pixels[i]);
            
int
blue = cm.getBlue(pixels[i]);
 
            
// 增加了图像的亮度
            
red = (
int
) (
1.1
* red +
30
);
            
green = (
int
) (
1.1
* green +
30
);
            
blue = (
int
) (
1.1
* blue +
30
);
            
if
(red >=
255
) {
                
red =
255
;
            
}
            
if
(green >=
255
) {
                
green =
255
;
            
}
            
if
(blue >=
255
) {
                
blue =
255
;
            
}
            
pixels[i] = alpha <<
24
| red <<
16
| green <<
8
| blue;
        
}
 
        
// 将数组中的象素产生一个图像
 
        
return
ImageIOHelper
                
.imageProducerToBufferedImage(
new
MemoryImageSource(iw, ih,
                        
pixels,
0
, iw));
    
}
 
    
/** 转换为黑白灰度图 */
    
public
BufferedImage grayFilter() {
        
ColorSpace cs = ColorSpace.getInstance(ColorSpace.CS_GRAY);
        
ColorConvertOp op =
new
ColorConvertOp(cs,
null
);
        
return
op.filter(image,
null
);
    
}
 
    
/** 平滑缩放 */
    
public
BufferedImage scaling(
double
s) {
        
AffineTransform tx =
new
AffineTransform();
        
tx.scale(s, s);
        
AffineTransformOp op =
new
AffineTransformOp(tx,
                
AffineTransformOp.TYPE_BILINEAR);
        
return
op.filter(image,
null
);
    
}
 
    
public
BufferedImage scale(Float s) {
        
int
srcW = image.getWidth();
        
int
srcH = image.getHeight();
        
int
newW = Math.round(srcW * s);
        
int
newH = Math.round(srcH * s);
        
// 先做水平方向上的伸缩变换
        
BufferedImage tmp =
new
BufferedImage(newW, newH, image.getType());
        
Graphics2D g = tmp.createGraphics();
        
for
(
int
x =
0
; x < newW; x++) {
            
g.setClip(x,
0
,
1
, srcH);
            
// 按比例放缩
            
g.drawImage(image, x - x * srcW / newW,
0
,
null
);
        
}
 
        
// 再做垂直方向上的伸缩变换
        
BufferedImage dst =
new
BufferedImage(newW, newH, image.getType());
        
g = dst.createGraphics();
        
for
(
int
y =
0
; y < newH; y++) {
            
g.setClip(
0
, y, newW,
1
);
            
// 按比例放缩
            
g.drawImage(tmp,
0
, y - y * srcH / newH,
null
);
        
}
        
return
dst;
    
}
 
}

转载于:https://www.cnblogs.com/leo3689/p/4419580.html

版权声明:本文内容由互联网用户自发贡献,该文观点仅代表作者本人。本站仅提供信息存储空间服务,不拥有所有权,不承担相关法律责任。如发现本站有涉嫌侵权/违法违规的内容, 请联系我们举报,一经查实,本站将立刻删除。

发布者:全栈程序员-站长,转载请注明出处:https://javaforall.net/109492.html原文链接:https://javaforall.net

(0)
上一篇 2021年9月5日 上午9:00
下一篇 2021年9月5日 上午10:00


相关推荐

  • 项目从 tomcat7部署到tomcat8「建议收藏」

    项目从 tomcat7部署到tomcat8「建议收藏」这段时间将一个老项目从tomcat7部署到tomcat8上,期间遇到的典型问题。接下来我会介绍下整个升级过程和在升级中遇到的问题。首先要装个jdk8+,因为开发环境用的是eclipse,还要搞个兼容tomcat8的eclipse.新下的tomcat8里是自带20几个jar的,这是要留着的不能直接拿来tomcat7的lib就用。因为老项目要依赖的jar都放在了tomcat下没有用maven,所以拿来…

    2022年7月18日
    29
  • redis的五种数据类型

    redis的五种数据类型一、百度百科1、简介(1)Redis(RemoteDictionaryServer远程字段服务)是一个开源的使用ANSIC语言编写、支持网络、科技与内存亦可持久化的日志型、key-value数据库,并提供多种语言的API。(2)Redis是一个key-value存储系统,它支持存储的value类型相对更多,包括string、list、set、zset(sortedset–有序集合)和hash。这些数据结构都支持push/pop、add/remove及取交集并集和差集及更丰富的操作,

    2022年6月17日
    21
  • 入门理解H264编码

    入门理解H264编码nbsp nbsp nbsp nbsp nbsp 最近入门音视频技术 一直在学习 H264 编解码标准 了解了不少关于 H264 的相关知识 对于网上各种类型的资料 始终没有找到一篇适合的知识梳理资料 可能是查找方式不对 所以花费了比较多的时间 经过一段时间的熟悉后结合网上各类大神的指导资料决定自己整理一下关于 H264 编解码标准的知识 以后方便自己查阅 也让更多刚入门的人提供一个参考资料 由于是新人 所以有些地方可能有理解不全面 望各位前

    2026年3月20日
    2
  • window10 安装_自己安装windows10

    window10 安装_自己安装windows10AppFabric简介WindowsServerAppFabric扩展了WindowsServer以为Web应用程序和中间层服务提供增强的托管、管理和缓存功能。AppFabric托管功能向Internet信息服务(IIS)、WindowsProcessActivationService(WAS)和.NETFramework4添加了服务管理扩展。其中包

    2022年10月17日
    6
  • 单射、满射、双射(一一映射)

    单射、满射、双射(一一映射)设函数f:X->Y,y=f(x)单射:任给x1和x2属于X,若x1≠x2,则f(x1)≠f(x2),称f为单射满射:任给y属于Y,都存在x属于X使得f(x)=y,称f为满射双射:若f既是单射又是满射,称f为双射,也叫一一对应。

    2022年5月1日
    337
  • 中国互联网金融协会发布风险提示,个人金融业务终端极其谨慎安装

    中国互联网金融协会发布风险提示,个人金融业务终端极其谨慎安装

    2026年3月15日
    3

发表回复

您的邮箱地址不会被公开。 必填项已用 * 标注

关注全栈程序员社区公众号