有没有人知道用于洪水填充的迭代且有效的算法？
或者有没有办法在没有堆栈溢出错误的情况下实现递归floodfill算法？
试了一个@ Flood fill using a stack 但我找不到一种方法来处理白色和黑色的图像。
答案 0 :(得分：29)
有人将J. Dunlap's队列线性洪水填充算法移植到了android here。我已经尝试过了，速度非常快。
我修改了最初使用作者未提供的名为Utilities的copyImage()方法。
public class QueueLinearFloodFiller {
protected Bitmap image = null;
protected int[] tolerance = new int[] { 0, 0, 0 };
protected int width = 0;
protected int height = 0;
protected int[] pixels = null;
protected int fillColor = 0;
protected int[] startColor = new int[] { 0, 0, 0 };
protected boolean[] pixelsChecked;
protected Queue<FloodFillRange> ranges;
// Construct using an image and a copy will be made to fill into,
// Construct with BufferedImage and flood fill will write directly to
// provided BufferedImage
public QueueLinearFloodFiller(Bitmap img) {
copyImage(img);
}
public QueueLinearFloodFiller(Bitmap img, int targetColor, int newColor) {
useImage(img);
setFillColor(newColor);
setTargetColor(targetColor);
}
public void setTargetColor(int targetColor) {
startColor[0] = Color.red(targetColor);
startColor[1] = Color.green(targetColor);
startColor[2] = Color.blue(targetColor);
}
public int getFillColor() {
return fillColor;
}
public void setFillColor(int value) {
fillColor = value;
}
public int[] getTolerance() {
return tolerance;
}
public void setTolerance(int[] value) {
tolerance = value;
}
public void setTolerance(int value) {
tolerance = new int[] { value, value, value };
}
public Bitmap getImage() {
return image;
}
public void copyImage(Bitmap img) {
// Copy data from provided Image to a BufferedImage to write flood fill
// to, use getImage to retrieve
// cache data in member variables to decrease overhead of property calls
width = img.getWidth();
height = img.getHeight();
image = Bitmap.createBitmap(width, height, Bitmap.Config.RGB_565);
Canvas canvas = new Canvas(image);
canvas.drawBitmap(img, 0, 0, null);
pixels = new int[width * height];
image.getPixels(pixels, 0, width, 1, 1, width - 1, height - 1);
}
public void useImage(Bitmap img) {
// Use a pre-existing provided BufferedImage and write directly to it
// cache data in member variables to decrease overhead of property calls
width = img.getWidth();
height = img.getHeight();
image = img;
pixels = new int[width * height];
image.getPixels(pixels, 0, width, 1, 1, width - 1, height - 1);
}
protected void prepare() {
// Called before starting flood-fill
pixelsChecked = new boolean[pixels.length];
ranges = new LinkedList<FloodFillRange>();
}
// Fills the specified point on the bitmap with the currently selected fill
// color.
// int x, int y: The starting coords for the fill
public void floodFill(int x, int y) {
// Setup
prepare();
if (startColor[0] == 0) {
// ***Get starting color.
int startPixel = pixels[(width * y) + x];
startColor[0] = (startPixel >> 16) & 0xff;
startColor[1] = (startPixel >> 8) & 0xff;
startColor[2] = startPixel & 0xff;
}
// ***Do first call to floodfill.
LinearFill(x, y);
// ***Call floodfill routine while floodfill ranges still exist on the
// queue
FloodFillRange range;
while (ranges.size() > 0) {
// **Get Next Range Off the Queue
range = ranges.remove();
// **Check Above and Below Each Pixel in the Floodfill Range
int downPxIdx = (width * (range.Y + 1)) + range.startX;
int upPxIdx = (width * (range.Y - 1)) + range.startX;
int upY = range.Y - 1;// so we can pass the y coord by ref
int downY = range.Y + 1;
for (int i = range.startX; i <= range.endX; i++) {
// *Start Fill Upwards
// if we're not above the top of the bitmap and the pixel above
// this one is within the color tolerance
if (range.Y > 0 && (!pixelsChecked[upPxIdx])
&& CheckPixel(upPxIdx))
LinearFill(i, upY);
// *Start Fill Downwards
// if we're not below the bottom of the bitmap and the pixel
// below this one is within the color tolerance
if (range.Y < (height - 1) && (!pixelsChecked[downPxIdx])
&& CheckPixel(downPxIdx))
LinearFill(i, downY);
downPxIdx++;
upPxIdx++;
}
}
image.setPixels(pixels, 0, width, 1, 1, width - 1, height - 1);
}
// Finds the furthermost left and right boundaries of the fill area
// on a given y coordinate, starting from a given x coordinate, filling as
// it goes.
// Adds the resulting horizontal range to the queue of floodfill ranges,
// to be processed in the main loop.
// int x, int y: The starting coords
protected void LinearFill(int x, int y) {
// ***Find Left Edge of Color Area
int lFillLoc = x; // the location to check/fill on the left
int pxIdx = (width * y) + x;
while (true) {
// **fill with the color
pixels[pxIdx] = fillColor;
// **indicate that this pixel has already been checked and filled
pixelsChecked[pxIdx] = true;
// **de-increment
lFillLoc--; // de-increment counter
pxIdx--; // de-increment pixel index
// **exit loop if we're at edge of bitmap or color area
if (lFillLoc < 0 || (pixelsChecked[pxIdx]) || !CheckPixel(pxIdx)) {
break;
}
}
lFillLoc++;
// ***Find Right Edge of Color Area
int rFillLoc = x; // the location to check/fill on the left
pxIdx = (width * y) + x;
while (true) {
// **fill with the color
pixels[pxIdx] = fillColor;
// **indicate that this pixel has already been checked and filled
pixelsChecked[pxIdx] = true;
// **increment
rFillLoc++; // increment counter
pxIdx++; // increment pixel index
// **exit loop if we're at edge of bitmap or color area
if (rFillLoc >= width || pixelsChecked[pxIdx] || !CheckPixel(pxIdx)) {
break;
}
}
rFillLoc--;
// add range to queue
FloodFillRange r = new FloodFillRange(lFillLoc, rFillLoc, y);
ranges.offer(r);
}
// Sees if a pixel is within the color tolerance range.
protected boolean CheckPixel(int px) {
int red = (pixels[px] >>> 16) & 0xff;
int green = (pixels[px] >>> 8) & 0xff;
int blue = pixels[px] & 0xff;
return (red >= (startColor[0] - tolerance[0])
&& red <= (startColor[0] + tolerance[0])
&& green >= (startColor[1] - tolerance[1])
&& green <= (startColor[1] + tolerance[1])
&& blue >= (startColor[2] - tolerance[2]) && blue <= (startColor[2] + tolerance[2]));
}
// Represents a linear range to be filled and branched from.
protected class FloodFillRange {
public int startX;
public int endX;
public int Y;
public FloodFillRange(int startX, int endX, int y) {
this.startX = startX;
this.endX = endX;
this.Y = y;
}
}
}
如果您不希望UI等待图像填充，您也可以使用线程。
public class FloodFillThread extends Thread {
ProgressDialog mProgressDialog;
Bitmap mBitmap;
int mTargetColor;
int mNewColor;
Point mPoint;
Runnable mCallback;
public FloodFillThread(ProgressDialog pd, Runnable callback, Bitmap bitmap,
Point pt, int targetColor, int newColor) {
mBitmap = bitmap;
mPoint = pt;
mTargetColor = targetColor;
mNewColor = newColor;
mProgressDialog = pd;
mCallback = callback;
}
@Override
public void run() {
QueueLinearFloodFiller filler = new QueueLinearFloodFiller(mBitmap, mTargetColor, mNewColor);
filler.setTolerance(10);
filler.floodFill(mPoint.x, mPoint.y);
handler.sendEmptyMessage(0);
}
private Handler handler = new Handler() {
@Override
public void handleMessage(Message msg) {
mProgressDialog.dismiss();
mCallback.run();
}
};
}
答案 1 :(得分：11)
排名最高的答案（由Shubhadeep Chaudhuri提供）无法处理透明背景。为此，您需要添加alpha检查。以下是执行此操作所需的更改：
更新私人会员
protected int[] tolerance = new int[] { 0, 0, 0, 0 };
protected int[] startColor = new int[] { 0, 0, 0, 0 };
更新方法
public void setTargetColor(int targetColor) {
/*Same as before....*/
startColor[3] = Color.alpha(targetColor);
}
public void setTolerance(int value) {
tolerance = new int[] { value, value, value, value };
}
protected boolean CheckPixel(int px) {
int red = (pixels[px] >>> 16) & 0xff;
int green = (pixels[px] >>> 8) & 0xff;
int blue = pixels[px] & 0xff;
int alpha = (Color.alpha(pixels[px]));
return (red >= (startColor[0] - tolerance[0]) && red <= (startColor[0] + tolerance[0])
&& green >= (startColor[1] - tolerance[1]) && green <= (startColor[1] + tolerance[1])
&& blue >= (startColor[2] - tolerance[2]) && blue <= (startColor[2] + tolerance[2])
&& alpha >= (startColor[3] - tolerance[3]) && alpha <= (startColor[3] + tolerance[3]));
}
答案 2 :(得分：7)
这个算法对我有用。
private void FloodFill(Bitmap bmp, Point pt, int targetColor, int replacementColor)
{
Queue<Point> q = new LinkedList<Point>();
q.add(pt);
while (q.size() > 0) {
Point n = q.poll();
if (bmp.getPixel(n.x, n.y) != targetColor)
continue;
Point w = n, e = new Point(n.x + 1, n.y);
while ((w.x > 0) && (bmp.getPixel(w.x, w.y) == targetColor)) {
bmp.setPixel(w.x, w.y, replacementColor);
if ((w.y > 0) && (bmp.getPixel(w.x, w.y - 1) == targetColor))
q.add(new Point(w.x, w.y - 1));
if ((w.y < bmp.getHeight() - 1)
&& (bmp.getPixel(w.x, w.y + 1) == targetColor))
q.add(new Point(w.x, w.y + 1));
w.x--;
}
while ((e.x < bmp.getWidth() - 1)
&& (bmp.getPixel(e.x, e.y) == targetColor)) {
bmp.setPixel(e.x, e.y, replacementColor);
if ((e.y > 0) && (bmp.getPixel(e.x, e.y - 1) == targetColor))
q.add(new Point(e.x, e.y - 1));
if ((e.y < bmp.getHeight() - 1)
&& (bmp.getPixel(e.x, e.y + 1) == targetColor))
q.add(new Point(e.x, e.y + 1));
e.x++;
}
}
}
答案 3 :(得分：4)
我上面的算法更快
使用getPixels()和setPixels()代替重复调用getPixel()。
但这里有一个tarde。
这个算法为数组int[bmp.width * bmp.height]使用了更多的内存空间。
private void floodFill_array(Bitmap bmp, Point pt, int targetColor, int replacementColor)
{
if(targetColor == replacementColor)
return;
int width, height;
int[] arrPixels;
width = bmp.getWidth();
height = bmp.getHeight();
arrPixels = new int[width*height];
bmp.getPixels(arrPixels, 0, width, 0, 0, width, height);
Queue<Point> q = new LinkedList<Point>();
q.add(pt);
while (q.size() > 0) {
Point n = q.poll();
if (arrPixels[width*n.y + n.x] != targetColor)
continue;
Point w = n, e = new Point(n.x + 1, n.y);
while ((w.x > 0) && (arrPixels[width*w.y + w.x] == targetColor)) {
arrPixels[width*w.y + w.x] = replacementColor; // setPixel
if ((w.y > 0) && (arrPixels[width*(w.y-1) + w.x] == targetColor))
q.add(new Point(w.x, w.y - 1));
if ((w.y < height - 1)
&& (arrPixels[width*(w.y+1) + w.x] == targetColor))
q.add(new Point(w.x, w.y + 1));
w.x--;
}
while ((e.x < width - 1)
&& (arrPixels[width*e.y + e.x] == targetColor)) {
arrPixels[width*e.y + e.x] = replacementColor; // setPixel
if ((e.y > 0) && (arrPixels[width*(e.y-1) + e.x] == targetColor))
q.add(new Point(e.x, e.y - 1));
if ((e.y < height - 1)
&& (arrPixels[width*(e.y+1) + e.x] == targetColor))
q.add(new Point(e.x, e.y + 1));
e.x++;
}
}
bmp.setPixels(arrPixels, 0, width, 0, 0, width, height);
}
如果您想使用“Tolerance”选项，请使用以下代码。
int minR, maxR, minG, maxG, minB, maxB; // instance values
private void floodFill_array(Bitmap bmp, Point pt, int targetColor, int replacementColor, int tolerance)
{
if(targetColor == replacementColor)
return;
/* tolerable values */
minR = ((targetColor & 0xFF0000) >> 16) - tolerance;
if(minR < 0) minR = 0;
else minR = minR << 16;
maxR = ((targetColor & 0xFF0000) >> 16) + tolerance;
if(maxR > 0xFF) maxR = 0xFF0000;
else maxR = maxR << 16;
minG = ((targetColor & 0x00FF00) >> 8) - tolerance;
if(minG < 0) minG = 0;
else minG = minG << 8;
maxG = ((targetColor & 0x00FF00) >> 8) + tolerance;
if(maxG > 0xFF) maxG = 0x00FF00;
else maxG = maxG << 8;
minB = (targetColor & 0x0000FF) - tolerance;
if(minB < 0) minB = 0;
maxB = (targetColor & 0x0000FF) + tolerance;
if(maxB > 0xFF) maxB = 0x0000FF;
/* tolerable values */
int width, height;
int[] arrPixels;
width = bmp.getWidth();
height = bmp.getHeight();
arrPixels = new int[width*height];
bmp.getPixels(arrPixels, 0, width, 0, 0, width, height);
Queue<Point> q = new LinkedList<Point>();
q.add(pt);
while (q.size() > 0) {
Point n = q.poll();
if(!isTolerable(arrPixels[width*n.y + n.x]))
continue;
Point w = n, e = new Point(n.x + 1, n.y);
while ((w.x > 0) && isTolerable(arrPixels[width*w.y + w.x])) {
arrPixels[width*w.y + w.x] = replacementColor; // setPixel
if ((w.y > 0) && isTolerable(arrPixels[width*(w.y-1) + w.x]))
q.add(new Point(w.x, w.y - 1));
if ((w.y < height - 1) && isTolerable(arrPixels[width*(w.y+1) + w.x]))
q.add(new Point(w.x, w.y + 1));
w.x--;
}
while ((e.x < width - 1) && isTolerable(arrPixels[width*e.y + e.x])) {
arrPixels[width*e.y + e.x] = replacementColor; // setPixel
if ((e.y > 0) && isTolerable(arrPixels[width*(e.y-1) + e.x]))
q.add(new Point(e.x, e.y - 1));
if ((e.y < height - 1) && isTolerable(arrPixels[width*(e.y+1) + e.x]))
q.add(new Point(e.x, e.y + 1));
e.x++;
}
}
bmp.setPixels(arrPixels, 0, width, 0, 0, width, height);
}
/**
* If the passed color is tolerable, return true.
*/
private boolean isTolerable(int currentColor){
int r = currentColor & 0xFF0000;
int g = currentColor & 0x00FF00;
int b = currentColor & 0x0000FF;
if(r<minR || r>maxR || g<minG || g>maxG || b<minB || b>maxB)
return false; // less than or grater than tolerable values
else
return true;
}
答案 4 :(得分：1)
使FloodFill()方法返回Bitmap对象更好。使它成为自定义View类的方法。你知道自定义View类有。 the onDraw(Canvas canvas)方法。在onDraw(Canvas c)中，使用FloodFill()，如下所示：
//resize the picture that you want to fill to fit the whole display.
bitmap=Bitmap.createScaledBitmap(bitmap, canvas.getWidth(),canvas.getHeight(), true);
/*get the same bitmap flood fill it. we reassign the bit map to iself to keep it for the next and another flood fill
currently_selected_point is a variable/object of type Point.
use the Point object to save your onTouchEvent(Event event) finger coordinates.
I used the Color.RED as a replacement color.
the target color is the color of the selected point currently_selected_point.
*/
bitmap=FloodFill(bitmap, currently_selected_point, bitmap.getPixel(currently_selected_point.x, currently_selected_point.y), Color.RED);
canvas.drawBitmap(bitmap,0,0, paint);
答案 5 :(得分：1)
调用数百或数千次的setPixel方法效率不高。最好通过JNI将算法移动到C ++。这是我可以使用的简单库。它比纯java实现快得多。
https://github.com/mar3kk/threekkapps_library/
只需致电
JniBitmap.floodFill(bitmap,x,y,color);