通过Emgu实现对图片上的数字进行识别。
前期步骤:
1.下载Emgu安装文件,我的版本是2.4.2.1777。3.0版本则实现对中文的支持。
2.安装后需填写环境变量,环境变量Path值后加入Emgu安装路径到bin下。如C:Emguemgucv-windows-x86-gpu 2.4.2.1777in;
3.在bin下查找需要的dll如Emgu.CV.dll与Emgu.CV.OCR.dll等。
4.将C:Emguemgucv-windows-x86-gpu 2.4.2.1777in下的文件夹tessdata赋值到程序运行目录下。
注:安装后的Emgu路径下有C#版本的demo可供参考
关键代码:
将需要的dll导入到项目中。
private static Tesseract _ocr;//创建识别对象
//传入图片进行识别 public static string ORC_(Bitmap img) { //""标示OCR识别调用失败 string re = ""; if (img == null) return re; else { Bgr drawColor = new Bgr(Color.Blue); try { Image<Bgr, Byte> image = new Image<Bgr, byte>(img); using (Image<Gray, byte> gray = image.Convert<Gray, Byte>()) { _ocr.Recognize(gray); Tesseract.Charactor[] charactors = _ocr.GetCharactors(); foreach (Tesseract.Charactor c in charactors) { image.Draw(c.Region, drawColor, 1); } re = _ocr.GetText(); } return re; } catch (Exception ex) { return re; } } } //识别方法如点击按钮识别 private void btnXIdentification_Click(object sender, EventArgs e) { try { _ocr = new Tesseract(@"C:Emguemgucv-windows-x86-gpu 2.4.2.1777in essdata", "eng", Tesseract.OcrEngineMode.OEM_TESSERACT_CUBE_COMBINED);//方法第一个参数可为""表示通过环境变量调用字库,第二个参数表示字库的文件,第三个表示识别方式,可看文档与资料查找。 _ocr.SetVariable("tessedit_char_whitelist", "0123456789X");//此方法表示只识别1234567890与x字母 string result = ""; Bitmap bitmap = new Bitmap(_emguImage.ToBitmap()); bitmap = BrightnessP(bitmap, Convert.ToInt32(this.textBoxX3.Text));//图片加亮处理 bitmap = KiContrast(bitmap, Convert.ToInt32(this.textBoxX2.Text));//调整对比对 this.pictureBox3.Image = bitmap; result = ORC_(bitmap); this.textBoxX1.Text = result; _ocr.Dispose(); } catch (Exception exception) { MessageBox.Show(exception.Message); } } /// <summary> /// 增加图像亮度 /// </summary> /// <param name="a"></param> /// <param name="v"></param> /// <returns></returns> public static Bitmap BrightnessP(Bitmap a, int v) { System.Drawing.Imaging.BitmapData bmpData = a.LockBits(new Rectangle(0, 0, a.Width, a.Height), System.Drawing.Imaging.ImageLockMode.ReadWrite, System.Drawing.Imaging.PixelFormat.Format24bppRgb); int bytes = a.Width * a.Height * 3; IntPtr ptr = bmpData.Scan0; int stride = bmpData.Stride; unsafe { byte* p = (byte*)ptr; int temp; for (int j = 0; j < a.Height; j++) { for (int i = 0; i < a.Width * 3; i++, p++) { temp = (int)(p[0] + v); temp = (temp > 255) ? 255 : temp < 0 ? 0 : temp; p[0] = (byte)temp; } p += stride - a.Width * 3; } } a.UnlockBits(bmpData); return a; } ///<summary> ///图像对比度调整 ///</summary> ///<param name="b">原始图</param> ///<param name="degree">对比度[-100, 100]</param> ///<returns></returns> public static Bitmap KiContrast(Bitmap b, int degree) { if (b == null) { return null; } if (degree < -100) degree = -100; if (degree > 100) degree = 100; try { double pixel = 0; double contrast = (100.0 + degree) / 100.0; contrast *= contrast; int width = b.Width; int height = b.Height; BitmapData data = b.LockBits(new Rectangle(0, 0, width, height), ImageLockMode.ReadWrite, PixelFormat.Format24bppRgb); unsafe { byte* p = (byte*)data.Scan0; int offset = data.Stride - width * 3; for (int y = 0; y < height; y++) { for (int x = 0; x < width; x++) { // 处理指定位置像素的对比度 for (int i = 0; i < 3; i++) { pixel = ((p / 255.0 - 0.5) * contrast + 0.5) * 255; if (pixel < 0) pixel = 0; if (pixel > 255) pixel = 255; p = (byte)pixel; } // i p += 3; } // x p += offset; } // y } b.UnlockBits(data); return b; } catch (Exception ex) { return null; } }
OEM_TESSERACT_ONLY, // Run Tesseract only - fastest运行只TESSERACT - 最快
OEM_CUBE_ONLY, // Run Cube only - better accuracy, but slower只运行立方 - 更好的精度,但速度较慢
OEM_TESSERACT_CUBE_COMBINED, // Run both and combine results - best accuracy运行和结果相结合 - 最佳精度
OEM_DEFAULT // Specify this mode when calling init_*(),指定此模式下,当调用init_*()