【C#】身份证识别（一）：身份证号定位

完整项目地址：https://gitee.com/xgpxg/ICRS

一、图像预处理

• 灰度化图像。
• 二值化图像。 利用 AdaptiveThresholdType 全局化阈值，blockSize = 55时，效果最好。

public static Image<Gray,byte> BinImg(Image <Bgr ,byte> img)        {            return img.Convert<Gray, byte>().ThresholdAdaptive(new Gray(255),                AdaptiveThresholdType.GaussianC,                ThresholdType.Binary,                55,                new Gray(55)).Erode(9);        }

二、身份证号区域提取

• 扩选图像黑色像素区域，形成连通区域。

img.Erode(9)

• 提取轮廓。

/// <summary>        /// 获取轮廓        /// </summary>        /// <param name="pic"></param>        /// <returns></returns>        private static  VectorOfVectorOfPoint GetContours(Image<Gray, byte> pic)        {            Image<Gray, byte> p1 = new Image<Gray, byte>(pic.Size);            Image<Gray, byte> p2 = pic.Canny(60, 255);            VectorOfVectorOfPoint contours = contours = new VectorOfVectorOfPoint();            CvInvoke.FindContours(p2, contours, p1, RetrType.Ccomp, ChainApproxMethod.ChainApproxSimple);            return contours;        }

• 轮廓筛选，提取身份证矩形区域。身份证号的宽高比约为8，将比值为7~9的轮廓保留，并绘制矩形

//筛选矩形 public static RotatedRect RotatedRect( Image<Bgr, byte> img)        {            Image<Bgr, byte> a = new Image<Bgr, byte>(img.Size);            VectorOfVectorOfPoint con = GetContours(BinImg(img));            Point[][] con1 = con.ToArrayOfArray();            PointF[][] con2 = Array.ConvertAll<Point[], PointF[]>(con1, new Converter<Point[], PointF[]>(PointToPointF));            for (int i = 0; i < con.Size; i++)            {                RotatedRect rrec = CvInvoke.MinAreaRect(con2[i]);                 float w = rrec.Size.Width;                float h = rrec.Size.Height;                  if (w / h > 6  &&  w / h < 10 && h > 20)                {                    PointF[] pointfs = rrec.GetVertices();                    for (int j = 0; j < pointfs.Length; j++)                        CvInvoke.Line(a, new Point((int)pointfs[j].X, (int)pointfs[j].Y), new Point((int)pointfs[(j + 1) % 4].X, (int)pointfs[(j + 1) % 4].Y), new MCvScalar(0, 0, 255, 255), 4);                    return rrec;                }            }            return new RotatedRect();        }//绘制矩形 public static void DrawRotatedRect(RotatedRect rrec, Image<Bgr,byte> img)        {            PointF[] pointfs = rrec.GetVertices();            for (int j = 0; j < pointfs.Length; j++)                CvInvoke.Line(img, new Point((int)pointfs[j].X, (int)pointfs[j].Y), new Point((int)pointfs[(j + 1) % 4].X, (int)pointfs[(j + 1) % 4].Y), new MCvScalar(0, 0, 255, 255), 4);        }

三、定位结果