直接用zego的SDK吧，web、iOS、Android都可以支持。有现成的demo和SDK试用
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下载一个安装版本的red5.执行exe文件将red5安装为系统服务.自己设置是否开机启动 或是自己在服务里启动 就不会有dos窗口
这个是linux吗？
有点看不懂··
猜2中方法：
添加commons-logging-1.1.1.jar
或者是：在red5的web.xml注释有log4J的配置
//运行以下程序即可
public class ImageInit {
BufferedImage image;
private int iw, ih;
private int[] pixels;
public ImageInit(BufferedImage image) {
this.image = image;
iw = image.getWidth();
ih = image.getHeight();
pixels = new int[iw * ih];
}
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 = 100;
// 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; // 通过移位重新构成某一点像素的RGB值
}
// 将数组中的象素产生一个图像
Image tempImg = Toolkit.getDefaultToolkit().createImage(
new MemoryImageSource(iw, ih, pixels, 0, iw));
image = new BufferedImage(tempImg.getWidth(null),
tempImg.getHeight(null), BufferedImage.TYPE_INT_BGR);
image.createGraphics().drawImage(tempImg, 0, 0, null);
return image;
}
public BufferedImage getMedian() {
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 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]);
// 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
Image tempImg = Toolkit.getDefaultToolkit().createImage(
new MemoryImageSource(iw, ih, pixels, 0, iw));
image = new BufferedImage(tempImg.getWidth(null),
tempImg.getHeight(null), BufferedImage.TYPE_INT_BGR);
image.createGraphics().drawImage(tempImg, 0, 0, null);
return image;
}
public BufferedImage getGrey() {
ColorConvertOp ccp = new ColorConvertOp(
ColorSpace.getInstance(ColorSpace.CS_GRAY), null);
return image = ccp.filter(image, null);
}
// Brighten using a linear formula that increases all color values
public BufferedImage getBrighten() {
RescaleOp rop = new RescaleOp(1.25f, 0, null);
return image = rop.filter(image, null);
}
// Blur by "convolving" the image with a matrix
public BufferedImage getBlur() {
float[] data = { .1111f, .1111f, .1111f, .1111f, .1111f, .1111f,
.1111f, .1111f, .1111f, };
ConvolveOp cop = new ConvolveOp(new Kernel(3, 3, data));
return image = cop.filter(image, null);
}
// Sharpen by using a different matrix
public BufferedImage getSharpen() {
float[] data = { 0.0f, -0.75f, 0.0f, -0.75f, 4.0f, -0.75f, 0.0f,
-0.75f, 0.0f };
ConvolveOp cop = new ConvolveOp(new Kernel(3, 3, data));
return image = cop.filter(image, null);
}
// 11) Rotate the image 180 degrees about its center point
public BufferedImage getRotate() {
AffineTransformOp atop = new AffineTransformOp(
AffineTransform.getRotateInstance(Math.PI,
image.getWidth() / 2, image.getHeight() / 2),
AffineTransformOp.TYPE_NEAREST_NEIGHBOR);
return image = atop.filter(image, null);
}
public BufferedImage getProcessedImg() {
return image;
}
public static void main(String[] args) throws IOException {
String filePath="F:/k7qp5.png";
FileInputStream fin = new FileInputStream(filePath);
BufferedImage bi = ImageIO.read(fin);
ImageInit flt = new ImageInit(bi);
flt.changeGrey();
flt.getGrey();
flt.getBrighten();
bi = flt.getProcessedImg();
String pname = filePath.substring(0, filePath.lastIndexOf("."));
File file = new File(pname + ".jpg");
ImageIO.write(bi, "jpg", file);
}
}
重庆分公司
重庆分公司
