使用QueueLinearFloodFillAlgorithm在着色中留下的空白

Question

我正在尝试在android中实现洪水填充算法。它的工作速度很慢，所以我根据这个链接尝试了队列线性洪水填充算法。

How to use flood fill algorithm in Android?

它工作得很快，但这部分还没有完全着色。在这张图片的边缘上还有一些空白。

​

我使用了以下代码：

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;
        }
    }
}

我试着增加容忍度值，但是仍然留下一些空白，如果我大幅度增加这个值，整个图像就会被着色。请帮帮我!

Answer 1

白色/灰色像素是抗混叠的结果，用于平滑线条的边缘。为了避免这些工件，您可以简单地在创建图像时不使用反混叠，或者您可以使用两步容忍度:一个较低的容限值用于传播洪水填充，另一个更高的值用于着色像素，但不进一步传播填充。

但这两种方法都会破坏图像的抗混叠性，降低图像质量。另一种方法是对图像进行另一次传递，并处理与填充相邻的像素( pixelsChecked为假的，但至少有一个pixelsChecked为真的邻域)，并计算一个反别名像素值，假设像素是针对一条黑线反别名的。

public boolean isFilled(int x, int y)
{
    if((x < 0) || (y < 0) || (x >= width) || (y >= height))
        return false;
    return pixelsChecked[(width * y) + x];
}

public boolean isNeighbourFilled(int x, int y)
{
    // return true if at least one neighbour is filled:
    for(int offsetY = -1; offsetY <= 1; offsetY++)
    {
        for(int offsetX = -1; offsetX <= 1; offsetX++)
        {
            if((offsetX != 0) && (offsetY != 0) &&
                isFilled(x + offsetX, y + offsetY))
                return true;
        }
    }
    return false;
}

public void antiAliasFillOutline()
{
    for(int y = 0; y < height; y++)
    {
        for(int x = 0; x < width; x++)
        {
            // if pixel is not filled by neighbour is then it's on the border
            if(!isFilled(x, y) && isNeighbourFilled(x, y))
            {
                // compute an anti-aliased pixel value:
                antiAliasPixel(x, y);
            }
        }
    }
}

public void antiAliasPixel(int x, int y)
{
    int pixel = pixels[(width * y) + x];
    int red = (pixel >>> 16) & 0xff;
    int green = (pixel >>> 8) & 0xff;
    int blue = pixel & 0xff;

    int fillred = (fillColor >>> 16) & 0xff;
    int fillgreen = (fillColor >>> 8) & 0xff;
    int fillblue = fillColor & 0xff;

    // work out how much to anti-alias from 0 to 256:
    int amount = ((red + green + blue) * 256) / 
        (startColor[0] + startColor[1] + startColor[2]);
    if(amount > 256)
        amount = 256;

    red = (fillred * amount) >> 8;
    green = (fillgreen * amount) >> 8;
    blue = (fillblue * amount) >> 8;

    pixels[(width * y) + x] = 0xff000000 | (red << 16) | (green << 8) | blue;
}

在洪水填埋场的末尾呼叫antiAliasFillOutline()。

您可以通过内联一些函数调用并删除对pixelsChecked的边界检查来加快它的速度(以牺牲可读性为代价)

public void antiAliasFillOutlineFaster()
{
    for(int y = 1; y < height - 1; y++)
    {
        int i = (y * width) + 1;
        for(int x = 1; x < width - 1; x++)
        {
            // if pixel is not filled by neighbour is then it's on the border
            if(!pixelsChecked[i] && 
                (pixelsChecked[i-1] || pixelsChecked[i+1] ||
                 pixelsChecked[i-width-1] || pixelsChecked[i-width] || pixelsChecked[i-width+1] ||
                 pixelsChecked[i+width-1] || pixelsChecked[i+width] || pixelsChecked[i+width+1]))
            {
                // compute an anti-aliased pixel value:
                antiAliasPixel(x, y);
            }
            i++;
        }
    }
}

您也可以尝试只检查4个相邻像素，而不是包括对角线在内的8个相邻像素。另外，像fillred等和(startColor[0] + startColor[1] + startColor[2])这样的值可以计算一次并存储在成员变量中。