public int getThreshold(NyARHistogram i_histogram)
{
//総ピクセル数を計算
int n = i_histogram.length;
int sum_of_pixel = i_histogram.total_of_data;
int[] hist = i_histogram.data;
// 閾値ピクセル数確定
int th_pixcels = sum_of_pixel * this._persentage / 100;
int th_wk;
int th_w, th_b;
// 黒点基準
th_wk = th_pixcels;
for (th_b = 0; th_b < n - 2; th_b++)
{
th_wk -= hist[th_b];
if (th_wk <= 0)
{
break;
}
}
// 白点基準
th_wk = th_pixcels;
for (th_w = n - 1; th_w > 1; th_w--)
{
th_wk -= hist[th_w];
if (th_wk <= 0)
{
break;
}
}
// 閾値の保存
return((th_w + th_b) / 2);
}
/**
* この関数は、SlidePTileを用いて敷居値を1個求めます。敷居値の範囲は、i_histogram引数の範囲と同じです。
*/
public int getThreshold(NyARHistogram i_histogram)
{
//総ピクセル数を計算
int n = i_histogram.length;
int sum_of_pixel = i_histogram.total_of_data;
int[] hist = i_histogram.data;
// 閾値ピクセル数確定
int th_pixcels = sum_of_pixel * this._persentage / 100;
int th_wk;
int th_w, th_b;
// 黒点基準
th_wk = th_pixcels;
for (th_b = 0; th_b < n - 2; th_b++)
{
th_wk -= hist[th_b];
if (th_wk <= 0)
{
break;
}
}
// 白点基準
th_wk = th_pixcels;
for (th_w = n - 1; th_w > 1; th_w--)
{
th_wk -= hist[th_w];
if (th_wk <= 0)
{
break;
}
}
// 閾値の保存
return (th_w + th_b) / 2;
}
/**
* 共通初期化関数。
* @param i_param
* @param i_drv_factory
* ラスタドライバのファクトリ。
* @param i_gs_type
* @param i_rgb_type
* @return
* @
*/
private void initInstance(NyARIntSize i_size)
{
//リソースの生成
this.initResource(i_size);
this._gs_hist = new NyARHistogram(256);
this._src_ts = 0;
this._gs_id_ts = 0;
this._gs_hist_ts = 0;
}
public NyARRasterThresholdAnalyzer_SlidePTile(int i_persentage,int i_raster_format,int i_vertical_interval)
{
Debug.Assert (0 <= i_persentage && i_persentage <= 50);
//初期化
if(!initInstance(i_raster_format,i_vertical_interval)){
throw new NyARException();
}
this._sptile=new NyARHistogramAnalyzer_SlidePTile(i_persentage);
this._histogram=new NyARHistogram(256);
}
public int getThreshold(NyARHistogram i_histogram)
{
int[] hist = i_histogram.data;
int n = i_histogram.length;
int da, sa, db, sb, dt, pt, st;
int i;
int th = 0;
//後で使う
dt = pt = 0;
for (i = 0; i < n; i++)
{
int h = hist[i];
dt += h * i;
pt += h * i * i; //正規化の時に使う定数
}
st = i_histogram.total_of_data;
//Low側(0<=i<=n-2)
da = dt;
sa = st;
//High側(i=n-1)
db = sb = 0;
double max = -1;
double max_mt = 0;
//各ヒストグラムの分離度を計算する(1<=i<=n-1の範囲で評価)
for (i = n - 1; i > 0; i--)
{
//次のヒストグラムを計算
int hist_count = hist[i];
int hist_val = hist_count * i;
da -= hist_val;
sa -= hist_count;
db += hist_val;
sb += hist_count;
//クラス間分散を計算
double dv = (sa + sb);
double mt = (double)(da + db) / dv;
double ma = (sa != 0?((double)da / (double)sa):0) - mt;
double mb = (sb != 0?((double)db / (double)sb):0) - mt;
double kai = ((double)(sa * (ma * ma) + sb * (mb * mb))) / dv;
if (max < kai)
{
max_mt = mt;
max = kai;
th = i;
}
//System.out.println(kai);
}
//max_mtを元に正規化
this._score = max / ((double)(pt + max_mt * max_mt * st - 2 * max_mt * dt) / st);//129,0.8888888888888887
return(th);
}
public NyARRasterThresholdAnalyzer_SlidePTile(int i_persentage, int i_raster_format, int i_vertical_interval)
{
Debug.Assert(0 <= i_persentage && i_persentage <= 50);
//初期化
if (!initInstance(i_raster_format, i_vertical_interval))
{
throw new NyARException();
}
this._sptile = new NyARHistogramAnalyzer_SlidePTile(i_persentage);
this._histogram = new NyARHistogram(256);
}
/**
* デバック用関数
* @param args
* main関数引数
*/
public static void main(string[] args)
{
NyARHistogram data = new NyARHistogram(256);
for (int i = 0; i < 256; i++)
{
data.data[i] = 128 - i > 0 ? 128 - i : i - 128;
}
data.total_of_data = data.getTotal(0, 255);
NyARHistogramAnalyzer_KittlerThreshold an = new NyARHistogramAnalyzer_KittlerThreshold();
int th = an.getThreshold(data);
//System.out.print(th);
return;
}
/**
* デバック用関数
* @param args
* main関数引数
*/
public static void main(string[] args)
{
NyARHistogram data = new NyARHistogram(256);
for (int i = 0; i < 256; i++)
{
data.data[i] = 128 - i > 0 ? 128 - i : i - 128;
}
data.total_of_data = data.getTotal(0, 255);
//NyARHistogramAnalyzer_KittlerThreshold an = new NyARHistogramAnalyzer_KittlerThreshold();
//int th = an.getThreshold(data);
//System.out.print(th);
return;
}
public int getThreshold(NyARHistogram i_histogram)
{
int[] hist=i_histogram.data;
int n=i_histogram.length;
int da,sa,db,sb,dt,pt,st;
int i;
int th=0;
//後で使う
dt=pt=0;
for(i=0;i<n;i++){
int h=hist[i];
dt+=h*i;
pt+=h*i*i;//正規化の時に使う定数
}
st=i_histogram.total_of_data;
//Low側(0<=i<=n-2)
da=dt;
sa=st;
//High側(i=n-1)
db=sb=0;
double max=-1;
double max_mt=0;
//各ヒストグラムの分離度を計算する(1<=i<=n-1の範囲で評価)
for(i=n-1;i>0;i--){
//次のヒストグラムを計算
int hist_count=hist[i];
int hist_val=hist_count*i;
da-=hist_val;
sa-=hist_count;
db+=hist_val;
sb+=hist_count;
//クラス間分散を計算
double dv=(sa+sb);
double mt=(double)(da+db)/dv;
double ma=(sa!=0?((double)da/(double)sa):0)-mt;
double mb=(sb!=0?((double)db/(double)sb):0)-mt;
double kai=((double)(sa*(ma*ma)+sb*(mb*mb)))/dv;
if(max<kai){
max_mt=mt;
max=kai;
th=i;
}
//System.out.println(kai);
}
//max_mtを元に正規化
this._score=max/((double)(pt+max_mt*max_mt*st-2*max_mt*dt)/st);//129,0.8888888888888887
return th;
}
/**
* o_histogramにヒストグラムを出力します。
* @param i_input
* @param o_histogram
* @return
* @throws NyARException
*/
public int analyzeRaster(INyARRaster i_input, NyARHistogram o_histogram)
{
NyARIntSize size = i_input.getSize();
//最大画像サイズの制限
Debug.Assert(size.w * size.h < 0x40000000);
Debug.Assert(o_histogram.length == 256); //現在は固定
int[] h = o_histogram.data;
//ヒストグラム初期化
for (int i = o_histogram.length - 1; i >= 0; i--)
{
h[i] = 0;
}
o_histogram.total_of_data = size.w * size.h / this._vertical_skip;
return(this._histImpl.createHistogram(i_input, size, h, this._vertical_skip));
}
public void analyzeRaster(INyARRaster i_input, NyARIntRect i_area, NyARHistogram o_histogram)
{
NyARIntSize size = i_input.getSize();
//最大画像サイズの制限
Debug.Assert(size.w * size.h < 0x40000000);
Debug.Assert(o_histogram.length == 256);//現在は固定
int[] h = o_histogram.data;
//ヒストグラム初期化
for (int i = o_histogram.length - 1; i >= 0; i--)
{
h[i] = 0;
}
o_histogram.total_of_data = i_area.w * i_area.h / this._vertical_skip;
this._histImpl.createHistogram(i_input, i_area.x, i_area.y, i_area.w, i_area.h, o_histogram.data, this._vertical_skip);
return;
}
public override void doFilter(INyARRaster i_input, INyARRaster i_output)
{
//ヒストグラムを得る
NyARHistogram hist = this._histogram;
this._hist_analyzer.analyzeRaster(i_input, hist);
//変換テーブルを作成
int hist_total = this._histogram.total_of_data;
int min = hist.getMinData();
int hist_size = this._histogram.length;
int sum = 0;
for (int i = 0; i < hist_size; i++)
{
sum += hist.data[i];
this.table[i] = (int)((sum - min) * (hist_size - 1) / ((hist_total - min)));
}
//変換
base.doFilter(i_input, i_output);
}
/**
* この関数は、kittlerThresholdを用いて敷居値を1個求めます。敷居値の範囲は、i_histogram引数の範囲と同じです。
*/
public int getThreshold(NyARHistogram i_histogram)
{
int i;
double min = Double.MaxValue;
int th = 0;
int da, sa, db, sb, pa, pb;
double oa, ob;
int[] hist = i_histogram.data;
int n = i_histogram.length;
//Low側
da = pa = 0;
int h;
for (i = 0; i < n; i++)
{
h = hist[i];
da += h * i; //i*h[i]
pa += h * i * i; //i*i*h[i]
}
sa = i_histogram.total_of_data;
//High側(i=n-1)
db = 0;
sb = 0;
pb = 0;
for (i = n - 1; i > 0; i--)
{
//次のヒストグラムを計算
int hist_count = hist[i]; //h[i]
int hist_val = hist_count * i; //h[i]*i
int hist_val2 = hist_val * i; //h[i]*i*i
da -= hist_val;
sa -= hist_count;
pa -= hist_val2;
db += hist_val;
sb += hist_count;
pb += hist_val2;
//初期化
double wa = (double)sa / (sa + sb);
double wb = (double)sb / (sa + sb);
if (wa == 0 || wb == 0)
{
continue;
}
oa = ob = 0;
double ma = sa != 0 ? (double)da / sa : 0;
//Σ(i-ma)^2*h[i]=Σ(i^2*h[i])+Σ(ma^2*h[i])-Σ(2*i*ma*h[i])
oa = ((double)(pa + ma * ma * sa - 2 * ma * da)) / sa;
double mb = sb != 0 ? (double)db / sb : 0;
//Σ(i-mb)^2*h[i]=Σ(i^2*h[i])+Σ(mb^2*h[i])-Σ(2*i*mb*h[i])
ob = ((double)(pb + mb * mb * sb - 2 * mb * db)) / sb;
double kai = wa * Math.Log(oa / wa) + wb * Math.Log(ob / wb);
if (kai > 0 && min > kai)
{
min = kai;
th = i;
}
//System.out.println(kai);
}
return(th);//129//7.506713872738873
}
/**
* この関数は、kittlerThresholdを用いて敷居値を1個求めます。敷居値の範囲は、i_histogram引数の範囲と同じです。
*/
public int getThreshold(NyARHistogram i_histogram)
{
int i;
double min = Double.MaxValue;
int th = 0;
int da, sa, db, sb, pa, pb;
double oa, ob;
int[] hist = i_histogram.data;
int n = i_histogram.length;
//Low側
da = pa = 0;
int h;
for (i = 0; i < n; i++)
{
h = hist[i];
da += h * i; //i*h[i]
pa += h * i * i; //i*i*h[i]
}
sa = i_histogram.total_of_data;
//High側(i=n-1)
db = 0;
sb = 0;
pb = 0;
for (i = n - 1; i > 0; i--)
{
//次のヒストグラムを計算
int hist_count = hist[i];//h[i]
int hist_val = hist_count * i; //h[i]*i
int hist_val2 = hist_val * i; //h[i]*i*i
da -= hist_val;
sa -= hist_count;
pa -= hist_val2;
db += hist_val;
sb += hist_count;
pb += hist_val2;
//初期化
double wa = (double)sa / (sa + sb);
double wb = (double)sb / (sa + sb);
if (wa == 0 || wb == 0)
{
continue;
}
oa = ob = 0;
double ma = sa != 0 ? (double)da / sa : 0;
//Σ(i-ma)^2*h[i]=Σ(i^2*h[i])+Σ(ma^2*h[i])-Σ(2*i*ma*h[i])
oa = ((double)(pa + ma * ma * sa - 2 * ma * da)) / sa;
double mb = sb != 0 ? (double)db / sb : 0;
//Σ(i-mb)^2*h[i]=Σ(i^2*h[i])+Σ(mb^2*h[i])-Σ(2*i*mb*h[i])
ob = ((double)(pb + mb * mb * sb - 2 * mb * db)) / sb;
double kai = wa * Math.Log(oa / wa) + wb * Math.Log(ob / wb);
if (kai > 0 && min > kai)
{
min = kai;
th = i;
}
//System.out.println(kai);
}
return th;//129//7.506713872738873
}
/**
* o_histogramにヒストグラムを出力します。
* @param i_input
* @param o_histogram
* @return
* @throws NyARException
*/
public int analyzeRaster(INyARRaster i_input,NyARHistogram o_histogram)
{
NyARIntSize size=i_input.getSize();
//最大画像サイズの制限
Debug.Assert(size.w*size.h<0x40000000);
Debug.Assert(o_histogram.length==256);//現在は固定
int[] h=o_histogram.data;
//ヒストグラム初期化
for (int i = o_histogram.length-1; i >=0; i--){
h[i] = 0;
}
o_histogram.total_of_data=size.w*size.h/this._vertical_skip;
return this._histImpl.createHistogram(i_input, size,h,this._vertical_skip);
}
