public static ConnectLevel connectLevel(this Image <Gray, Byte> src, int curLv, int level, int padding)
{
ConnectLevel conn = new ConnectLevel {
Level = curLv
};
int width = src.Width, height = src.Height;
var visit = new bool[height, width];
int grade = 256 / level, color = conn.Level * grade;
for (int i = padding; i < height - padding; ++i)
{
for (int j = padding; j < width - padding; ++j)
{
if (visit[i, j])
{
continue;
}
Point p = new Point(j, i);
if (src[i, j].Intensity < color)
{
conn.NotIn.Add(p);
}
else
{
bfsSearch(src, visit, conn, p, color, padding);
}
}
}
double[] stats = Stats.CalcMeansAndVariance(conn.Domains.Select(c => (double)c.Area).ToArray());
conn.MeanArea = stats[0];
conn.Variance = stats[1];
return(conn);
}
public static ConnectLevel[] Connect(this Image <Gray, Byte> src, int level)
{
var result = new ConnectLevel[level];
for (int i = 0; i < level; ++i)
{
result[i] = connectLevel(src, i, level, 1);
}
return(result);
}
public static Image<Bgr, Byte> ColorLevel(this Image<Gray, Byte> src, ConnectLevel conn)
{
var dst = src.Convert<Bgr, Byte>();
var color = new Bgr(0, 0, 255);
foreach (var domain in conn.Domains) {
foreach (var p in domain.Points) {
dst[p.Y, p.X] = color;
}
}
return dst;
}
private static int bfsSearch(Image <Gray, Byte> img, bool[,] vi, ConnectLevel conn, Point start, int color, int padding)
{
if (vi[start.Y, start.X])
{
return(0);
}
var domain = new ConnectDomain();
Queue <Point> queue = new Queue <Point>();
queue.Enqueue(start);
var dir = DirVec;
while (queue.Count > 0)
{
Point p = queue.Dequeue();
if (vi[p.Y, p.X])
{
continue;
}
vi[p.Y, p.X] = true;
domain.Add(p);
for (int i = 0; i < connect; ++i)
{
int ny = p.Y + dir[i, 1], nx = p.X + dir[i, 0];
if (ny < padding || ny >= img.Height - padding)
{
continue;
}
if (nx < padding || nx >= img.Width - padding)
{
continue;
}
if (vi[ny, nx])
{
continue; // 提前判断一下，好选择加入哪个集合
}
Point np = new Point(nx, ny);
if (img[ny, nx].Intensity >= color)
{
queue.Enqueue(np);
}
else
{
conn.NotIn.Add(np);
}
}
}
conn.AddDomain(domain);
return(domain.Area);
}
public static Image <Bgr, Byte> ColorLevel(this Image <Gray, Byte> src, ConnectLevel conn)
{
var dst = src.Convert <Bgr, Byte>();
var color = new Bgr(0, 0, 255);
foreach (var domain in conn.Domains)
{
foreach (var p in domain.Points)
{
dst[p.Y, p.X] = color;
}
}
return(dst);
}
public static ConnectLevel connectLevel(this Image<Gray, Byte> src, int curLv, int level, int padding)
{
ConnectLevel conn = new ConnectLevel { Level = curLv };
int width = src.Width, height = src.Height;
var visit = new bool[height, width];
int grade = 256 / level, color = conn.Level * grade;
for (int i = padding; i < height - padding; ++i) {
for (int j = padding; j < width - padding; ++j) {
if (visit[i, j]) continue;
Point p = new Point(j, i);
if (src[i, j].Intensity < color) {
conn.NotIn.Add(p);
} else {
bfsSearch(src, visit, conn, p, color, padding);
}
}
}
double[] stats = Stats.CalcMeansAndVariance(conn.Domains.Select(c => (double)c.Area).ToArray());
conn.MeanArea = stats[0];
conn.Variance = stats[1];
return conn;
}
public static ConnectLevel[] Connect(this Image<Gray, Byte> src, int level)
{
var result = new ConnectLevel[level];
for (int i = 0; i < level; ++i) {
result[i] = connectLevel(src, i, level, 1);
}
return result;
}
private static int bfsSearch(Image<Gray, Byte> img, bool[,] vi, ConnectLevel conn, Point start, int color, int padding)
{
if (vi[start.Y, start.X]) return 0;
var domain = new ConnectDomain();
Queue<Point> queue = new Queue<Point>();
queue.Enqueue(start);
var dir = DirVec;
while (queue.Count > 0) {
Point p = queue.Dequeue();
if (vi[p.Y, p.X]) continue;
vi[p.Y, p.X] = true;
domain.Add(p);
for (int i = 0; i < connect; ++i) {
int ny = p.Y + dir[i, 1], nx = p.X + dir[i, 0];
if (ny < padding || ny >= img.Height - padding) continue;
if (nx < padding || nx >= img.Width - padding) continue;
if (vi[ny, nx]) continue; // 提前判断一下，好选择加入哪个集合
Point np = new Point(nx, ny);
if (img[ny, nx].Intensity >= color) {
queue.Enqueue(np);
} else {
conn.NotIn.Add(np);
}
}
}
conn.AddDomain(domain);
return domain.Area;
}
