如何在Java中自动裁剪图像白色边框？

Question

什么是最简单的方法来自动从Java中的图像裁剪白色边框？在此先感谢...

Answer 1

如果你想白色部分是无形的，最好的办法是用图像过滤器，使白色像素透明的，它是通过discussed here与@PhiLho一些很好的示例， 如果要调整你的图片所以它的边框不会有白色，你可以用四个简单的循环来做， 这个我为你写的小方法就是诀窍，注意它只是裁剪图片的上半部分，你可以写休息，

private Image getCroppedImage(String address) throws IOException{ 
    BufferedImage source = ImageIO.read(new File(address)) ; 

    boolean flag = false ; 
    int upperBorder = -1 ; 
    do{ 
     upperBorder ++ ; 
     for (int c1 =0 ; c1 < source.getWidth() ; c1++){ 
      if(source.getRGB(c1, upperBorder) != Color.white.getRGB()){ 
       flag = true; 
       break ; 
      } 
     } 

     if (upperBorder >= source.getHeight()) 
      flag = true ; 
    }while(!flag) ; 

    BufferedImage destination = new BufferedImage(source.getWidth(), source.getHeight() - upperBorder, BufferedImage.TYPE_INT_ARGB) ; 
    destination.getGraphics().drawImage(source, 0, upperBorder*-1, null) ; 

    return destination ; 
} 

Answer 2

这里的裁剪所有4个方面的方式，利用颜色从最左上角的像素为基准，并允许颜色变化的耐受性，从而在IM的噪音年龄不会使作物无用

public BufferedImage getCroppedImage(BufferedImage source, double tolerance) { 
    // Get our top-left pixel color as our "baseline" for cropping 
    int baseColor = source.getRGB(0, 0); 

    int width = source.getWidth(); 
    int height = source.getHeight(); 

    int topY = Integer.MAX_VALUE, topX = Integer.MAX_VALUE; 
    int bottomY = -1, bottomX = -1; 
    for(int y=0; y<height; y++) { 
     for(int x=0; x<width; x++) { 
     if (colorWithinTolerance(baseColor, source.getRGB(x, y), tolerance)) { 
      if (x < topX) topX = x; 
      if (y < topY) topY = y; 
      if (x > bottomX) bottomX = x; 
      if (y > bottomY) bottomY = y; 
     } 
     } 
    } 

    BufferedImage destination = new BufferedImage((bottomX-topX+1), 
       (bottomY-topY+1), BufferedImage.TYPE_INT_ARGB); 

    destination.getGraphics().drawImage(source, 0, 0, 
       destination.getWidth(), destination.getHeight(), 
       topX, topY, bottomX, bottomY, null); 

    return destination; 
} 

private boolean colorWithinTolerance(int a, int b, double tolerance) { 
    int aAlpha = (int)((a & 0xFF000000) >>> 24); // Alpha level 
    int aRed = (int)((a & 0x00FF0000) >>> 16); // Red level 
    int aGreen = (int)((a & 0x0000FF00) >>> 8); // Green level 
    int aBlue = (int)(a & 0x000000FF);   // Blue level 

    int bAlpha = (int)((b & 0xFF000000) >>> 24); // Alpha level 
    int bRed = (int)((b & 0x00FF0000) >>> 16); // Red level 
    int bGreen = (int)((b & 0x0000FF00) >>> 8); // Green level 
    int bBlue = (int)(b & 0x000000FF);   // Blue level 

    double distance = Math.sqrt((aAlpha-bAlpha)*(aAlpha-bAlpha) + 
           (aRed-bRed)*(aRed-bRed) + 
           (aGreen-bGreen)*(aGreen-bGreen) + 
           (aBlue-bBlue)*(aBlue-bBlue)); 

    // 510.0 is the maximum distance between two colors 
    // (0,0,0,0 -> 255,255,255,255) 
    double percentAway = distance/510.0d;  

    return (percentAway > tolerance); 
} 

Answer 3

而这里只是一个例子

private static BufferedImage autoCrop(BufferedImage sourceImage) { 
    int left = 0; 
    int right = 0; 
    int top = 0; 
    int bottom = 0; 
    boolean firstFind = true; 
    for (int x = 0; x < sourceImage.getWidth(); x++) { 
     for (int y = 0; y < sourceImage.getWidth(); y++) { 
      // pixel is not empty 
      if (sourceImage.getRGB(x, y) != 0) { 

       // we walk from left to right, thus x can be applied as left on first finding 
       if (firstFind) { 
        left = x; 
       } 

       // update right on each finding, because x can grow only 
       right = x; 

       // on first find apply y as top 
       if (firstFind) { 
        top = y; 
       } else { 
        // on each further find apply y to top only if a lower has been found 
        top = Math.min(top, y); 
       } 

       // on first find apply y as bottom 
       if (bottom == 0) { 
        bottom = y; 
       } else { 
        // on each further find apply y to bottom only if a higher has been found 
        bottom = Math.max(bottom, y); 
       } 
       firstFind = false; 
      } 
     } 
    } 

    return sourceImage.getSubimage(left, top, right - left, bottom - top); 
}