gistfile1.cs

static IplImage FaceDe(IplImage srcImg)
        {
            const double Scale = 1.04;
            const double ScaleFactor = 1.139;
            const int MinNeighbors = 2;


            using (IplImage smallImg = new IplImage(new CvSize(Cv.Round(srcImg.Width / Scale), Cv.Round(srcImg.Height / Scale)), BitDepth.U8, 1))
            {
                // 顔検出用の画像の生成
                using (IplImage gray = new IplImage(srcImg.Size, BitDepth.U8, 1))
                {
                    Cv.CvtColor(srcImg, gray, ColorConversion.BgrToGray);
                    Cv.Resize(gray, smallImg, Interpolation.Linear);
                    Cv.EqualizeHist(smallImg, smallImg);
                }

                //using (CvHaarClassifierCascade cascade = Cv.Load<CvHaarClassifierCascade>(Const.XmlHaarcascade))  // どっちでも可
                using (CvHaarClassifierCascade cascade = CvHaarClassifierCascade.FromFile("C:\\haarcascade_frontalface_alt.xml"))    // 
                using (CvMemStorage storage = new CvMemStorage())
                {
                    storage.Clear();

                    // 顔の検出
                    CvSeq<CvAvgComp> faces = Cv.HaarDetectObjects(smallImg, cascade, storage, ScaleFactor, MinNeighbors, 0, new CvSize(30, 30));

                    // モザイク処理
                    for (int d = 0; d < faces.Total; d++)
                    {
                        CvRect r = faces[d].Value.Rect;
                        Cv.Rectangle(srcImg, r, new CvScalar( 0x00FFFF ) );
                    }
                    return srcImg;
                }
            }
        }