[函數名稱]
二值圖像細化算法 WriteableBitmap ThinningProcess(WriteableBitmap src)
[算法說明]
圖像細化(Image Thinning),一般指二值圖像的骨架化(Image Skeletonization)的一種操作運算。所謂的細化就是經過一層層的剝離,從原來的圖中去掉一些點,但仍要保持原來的形狀,直到得到圖像的骨架。骨架,可以理解為圖象的中軸。
細化算法有很多,我們這裡介紹一種二值圖像的快速細化算法—Zhang 細化算法,該算法是Zhang於1984年提出。
算法過程如下:
1,設二值圖像中0為背景,1為目標。目標像素的8鄰域如下圖所示:
2,對於當前點P1,我們判斷以下7個條件:
(1)p1=1;
(2)2<=N(p1)<=6;
(3)T(p1)=1;
(4)p2*p4*p6=0;
(5)p4*p6*p8=0;
(6)p2(p4*p8=0;
(7)p2*p6*p8=0;
其中,N(p1)表示p1像素的8鄰域像素中目標像素的個數;T(p1)表示像素p1-p9中,像素值從0變換到1的次數。
對於p1,如果滿足(1)&(2)&(3)&[(4)&(5)||(6)&(7)]時,將p1像素標記為背景像素0。
將以上判斷作為1次迭代過程進行迭代,如果當前圖像中不存在可以標記為背景的像素p1時,迭代結束,細化完成。
Zhang快速細化算法有一個缺點:細化後的圖像不一定是單像素的骨架。
本文代碼中以1為背景,0為目標。
- [函數代碼]
- /// <summary>
- /// Zhang's fast thinning process for binary image.
- /// </summary>
- /// <param name="src">The source image.</param>
- /// <returns></returns>
- public static WriteableBitmap ThinningProcess(WriteableBitmap src)////二值圖像細化(Zhang快速細化算法)
- {
- if (src != null)
- {
- int w = src.PixelWidth;
- int h = src.PixelHeight;
- WriteableBitmap srcImage = new WriteableBitmap(w, h);
- byte[] temp = src.PixelBuffer.ToArray();
- byte[] tempMask = (byte[])temp.Clone();
- int[,] srcBytes = new int[w, h];
- for (int j = 0; j < h; j++)
- {
- for (int i = 0; i < w ; i++)
- {
- srcBytes[i, j] = (tempMask[i * 4 + j * w * 4] * 0.114 + tempMask[i * 4 + 1 + j * w * 4] * 0.587 + tempMask[i * 4 + 2 + j * w * 4] * 0.299 < 128 ? 0 : 1);
- }
- }
- Thinning(ref srcBytes, w, h);
- for (int j = 0; j < h; j++)
- {
- for (int i = 0; i < w; i++)
- {
- temp[i * 4 + j * w * 4] = temp[i * 4 + 1 + j * w * 4] = temp[i * 4 + 2 + j * w * 4] = (byte)(srcBytes[i, j] * 255);
- }
- }
- Stream sTemp = srcImage.PixelBuffer.AsStream();
- sTemp.Seek(0, SeekOrigin.Begin);
- sTemp.Write(temp, 0, w * 4 * h);
- return srcImage;
- }
- else
- {
- return null;
- }
- }
- private static void Thinning(ref int[,] srcBytes,int w,int h)
- {
- int[] srcTemp;
- int countNumber;
- do
- {
- countNumber = 0;
- for (int y = 1; y < h - 1; y++)
- {
- for (int x = 1; x < w - 1; x++)
- {
- srcTemp = new int[9] { srcBytes[x, y], srcBytes[x - 1, y - 1], srcBytes[x, y - 1], srcBytes[x + 1, y - 1], srcBytes[x + 1, y], srcBytes[x + 1, y + 1], srcBytes[x, y + 1], srcBytes[x - 1, y + 1], srcBytes[x - 1, y] };
- if (srcBytes[x, y] != 1)
- {
- if (CountN(srcTemp) >= 2 && CountN(srcTemp) <= 6)
- {
- if (CountT(srcTemp) == 1)
- {
- if (srcBytes[x, y - 1] * srcBytes[x + 1, y] * srcBytes[x, y + 1] == 0)
- {
- if (srcBytes[x - 1, y] * srcBytes[x + 1, y] * srcBytes[x, y + 1] == 0)
- {
- srcBytes[x, y] = (byte)1;
- countNumber++;
- }
- }
- else
- {
- if (srcBytes[x, y - 1] * srcBytes[x + 1, y] * srcBytes[x - 1, y] == 0)
- {
- if (srcBytes[x, y - 1] * srcBytes[x, y + 1] * srcBytes[x - 1, y] == 0)
- {
- srcBytes[x, y] = (byte)1;
- countNumber++;
- }
- }
- }
- }
- }
- }
- }
- }
- } while (countNumber != 0);
- }
- private static int CountN(params int[] src)
- {
- int count = 0;
- for (int i = 0; i < src.Length; i++)
- {
- if (src[i] == 0)
- {
- count++;
- }
- }
- return count;
- }
- private static int CountT(params int[] src)
- {
- int count = 0;
- for (int i = 1; i < src.Length; i++)
- {
- if (src[i] == 1 && src[i - 1] == 0)
- {
- count++;
- }
- }
- if (src[src.Length - 1] == 0 && src[0] == 1)
- {
- count++;
- }
- return count;
- }
[圖像效果]
全站熱搜