1. 全栈程序员必看首页

验证码图片

全栈程序员-站长 • • 未分类 • 阅读 62

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

赞 (0)
全栈程序员-站长的头像全栈程序员-站长
0 0


相关推荐

  • 00后程序员摸爬滚打近一年，为学弟学妹们总结出了以下 7 条人生建议（建议收藏）

    00后程序员摸爬滚打近一年，为学弟学妹们总结出了以下 7 条人生建议（建议收藏）

    作为一名“00后”，带你分享一下我内心的世界…..

    全栈程序员-站长的头像 全栈程序员-站长
    2022年4月6日
    63
  • GET和POST两种基本请求方法的区别「建议收藏」

    GET和POST两种基本请求方法的区别「建议收藏」

    GET和POST两种基本请求方法的区别「建议收藏」GET和POST是HTTP请求的两种基本方法，要说它们的区别，接触过WEB开发的人都能说出一二。最直观的区别就是GET把参数包含在URL中，POST通过request body传递参数。你可能自己写过无数个GET和POST请求，或者已经看过很多权威网站总结出的他们的区别，你非常清楚知道什么时候该用什么。当你在面试中被问到这个问题，你的内心充满了自信和喜悦。 你轻轻松松的给出…

    全栈程序员-站长的头像 全栈程序员-站长
    2022年6月13日
    39
  • SM4加密解密_iunlocker解锁网站

    SM4加密解密_iunlocker解锁网站

    SM4加密解密_iunlocker解锁网站最近工作需要用到SM4加密解密算法，所以研究了一下。内容主要参考自：https://blog.csdn.net/weixin_34411563/article/details/86000381首先介绍一下SM4加密算法SM4是我们自己国家的一个分组密码算法，是国家密码管理局于2012年发布的。http://www.cnnic.net.cn/jscx/mixbz/sm4/，具体的加密很麻…

    全栈程序员-站长的头像 全栈程序员-站长
    2022年10月6日
    3
  • 关于程序多开的尝试。CreateMutex，OpenMuxtex，ReleaseMutex「建议收藏」

    关于程序多开的尝试。CreateMutex，OpenMuxtex，ReleaseMutex「建议收藏」

    关于程序多开的尝试。CreateMutex，OpenMuxtex，ReleaseMutex「建议收藏」因为偶尔会遇到对那些不能支持双开的程序进行多开。。根据前一阵转的一篇文件了解到，现在大多程序都用CreateMutex方式来限制多开，于是有个想法：它Create了，我Release它，然后不就可以多开了吗？然而。。。经过一些小程序的验证及网上的搜索，我失败了。原因是：对于一个Mutex来说，只有Create它的进程才可以Release它。所以想用这种方式是不可能了。不过并不是…

    全栈程序员-站长的头像 全栈程序员-站长
    2022年6月26日
    26
  • <span>局部敏感哈希(Locality-Sensitive Hashing, LSH)</span>

    局部敏感哈希(Locality-Sensitive Hashing, LSH)

    局部敏感哈希(Locality-Sensitive Hashing, LSH)

    全栈程序员-站长的头像 全栈程序员-站长
    2021年11月22日
    49
  • java用户态和内核态「建议收藏」

    java用户态和内核态「建议收藏」

    java用户态和内核态「建议收藏」在&lt;深入理解java虚拟机&gt;这本书上多次看到用户态和内核态两个名词,虽然大概能明白意思.但对于两者具体的定义和区别还是比较,特此查阅之后记录.内核态(KernelMode)与用户态(UserMode)内核态:CPU可以访问内存所有数据,包括外围设备,例如硬盘,网卡.CPU也可以将自己从一个程序切换到另一个程序用户态:只能受限的访问内存,且不允许访问外…

    全栈程序员-站长的头像 全栈程序员-站长
    2026年1月14日
    5

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