一、先在halcon中实现ocr识别
所要识别的图如下：
*联合vc时要用绝对路径
read_image (Image, 'C://Users//Administrator//Desktop/halcon//第九讲、halcon联合vc实现ocr识别//1.png')
get_image_size (Image, Width, Height)
dev_open_window (0, 0, Width, Height, 'black', WindowHandle)
dev_display (Image)
*定位校正
words:=['S','K','2','1','3','0','A','0','4','0','6','2','0']
gen_rectangle1 (ROI_0, 168.5, 16.5, 379.5, 608.5)
text_line_orientation (ROI_0, Image, 25, -0.523599, 0.523599, OrientationAngle)
area_center (ROI_0, Area, Row, Column)
vector_angle_to_rigid (Row, Column, OrientationAngle, Row, Column, 0, HomMat2D)
affine_trans_image (Image, ImageAffinTrans, HomMat2D, 'constant', 'false')
*获得点图，点的半径为5，偏移量为2，感兴趣点为黑色点
dots_image (ImageAffinTrans, DotImage,5, 'dark',2)
gen_rectangle1 (ROI_0, 195.5, 14.5, 355.5, 612.5)
reduce_domain (DotImage, ROI_0, ImageReduced)
threshold (ImageReduced, Regions, 20, 255)
*形态学运算
gen_rectangle2 (Rectangle1, 0, 0, rad(45), 8, 4)
closing (Regions, Rectangle1, RegionClosing)
gen_rectangle2 (Rectangle2, 0, 0, rad(145), 8, 4)
closing (RegionClosing, Rectangle2, RegionClosing)
dilation_circle (RegionClosing, RegionDilation1, 4.5)
connection (RegionDilation1, ConnectedRegions)
select_shape (ConnectedRegions, SelectedRegions, 'area', 'and', 985.32, 2000.01)
*动态分割
partition_dynamic (SelectedRegions, Partitioned, 60, 20)
sort_region (Partitioned, SortedRegions, 'character', 'true', 'row')
count_obj (SortedRegions, Number)
*创建trf训练文件
for i:=1 to Number by 1
select_obj (SortedRegions, ObjectSelected, i)
*区域和区域作交集
intersection (ObjectSelected, Regions, RegionIntersection)
append_ocr_trainf (RegionIntersection, ImageAffinTrans, words[i-1], 'C://Users//Administrator//Desktop/halcon//第九讲、halcon联合vc实现ocr识别//train_ocr')
*disp_continue_message (WindowHandle, 'black', 'true')
*stop()
endfor
read_ocr_trainf_names ('C://Users//Administrator//Desktop/halcon//第九讲、halcon联合vc实现ocr识别//train_ocr', CharacterNames, CharacterCount)
create_ocr_class_mlp (8, 10, 'constant', 'default', CharacterNames, 80, 'none', 10, 42, OCRHandle)
trainf_ocr_class_mlp (OCRHandle, 'C://Users//Administrator//Desktop/halcon//第九讲、halcon联合vc实现ocr识别//train_ocr.trf', 200, 1, 0.01, Error, ErrorLog)
*也可直接读入halcon训练好的模型文件，则上面的创建训练文件、分类器以及训练都可以不要了
* read_ocr_class_mlp ('Industrial_0-9A-Z_NoRej.omc', OCRHandle)
intersection (SortedRegions, Regions, RegionIntersection1)
do_ocr_multi_class_mlp (RegionIntersection1, ImageAffinTrans, OCRHandle, Class, Confidence)
smallest_rectangle1 (RegionIntersection1, Row1, Column1, Row2, Column2)
set_display_font (WindowHandle, 26, 'mono', 'true', 'false')
dev_display (ImageAffinTrans)
for j:=0 to Number-1 by 1
disp_message (WindowHandle, Class[j], 'image', Row1[j]+120, Column1[j], 'white', 'false')
endfor
用自己训练的模型识别结果如下 ：
用halcon自带的模型识别结果如下：
二、halcon联合vc实现ocr识别
1、新建MFC工程；
2、进行配置，halcon在vc中的配置在我的上一篇博客有所讲解；
3、删除默认控件，添加自己需要的控件；
4、为button按钮添加消息响应函数，将action里的代码拷贝到里面，因为需要显示所以还需要拷贝显示函数；
5、最后我们需要把结果显示到编辑框中，事件要有行为，需要由变量来实现，所以还需要为编辑控件添加一个变量。
void CMFCApplication2Dlg::OnBnClickedButton1()
{
// Local iconic variables
HObject ho_Image, ho_ROI_0, ho_ImageAffinTrans;
HObject ho_DotImage, ho_ImageReduced, ho_Regions, ho_Rectangle1;
HObject ho_RegionClosing, ho_Rectangle2, ho_RegionDilation1;
HObject ho_ConnectedRegions, ho_SelectedRegions, ho_Partitioned;
HObject ho_SortedRegions, ho_ObjectSelected, ho_RegionIntersection;
HObject ho_RegionIntersection1;
// Local control variables
HTuple hv_Width, hv_Height, hv_WindowHandle;
HTuple hv_words, hv_OrientationAngle, hv_Area, hv_Row;
HTuple hv_Column, hv_HomMat2D, hv_Number, hv_i, hv_CharacterNames;
HTuple hv_CharacterCount, hv_OCRHandle, hv_Error, hv_ErrorLog;
HTuple hv_Class, hv_Confidence, hv_Row1, hv_Column1, hv_Row2;
HTuple hv_Column2, hv_j;
HTuple kuan, gao;
ReadImage(&ho_Image, "C://Users//Administrator//Desktop/halcon//第九讲、halcon联合vc实现ocr识别//1.png");
GetImageSize(ho_Image, &hv_Width, &hv_Height);
SetWindowAttr("background_color", "black");
//【***】关联显示窗口
HWND hwnd;
hwnd = GetDlgItem(PIC)->m_hWnd;
LONG windowID = (LONG)hwnd;
CRect rect;
GetDlgItem(PIC)->GetWindowRect(&rect);
kuan[0] = rect.Width();
gao[0] = rect.Height();
OpenWindow(0, 0, kuan[0], gao[0], windowID, "", "", &hv_WindowHandle);
HDevWindowStack::Push(hv_WindowHandle);
if (HDevWindowStack::IsOpen())
DispObj(ho_Image, HDevWindowStack::GetActive());
//定位校正
hv_words.Clear();
hv_words[0] = "S";
hv_words[1] = "K";
hv_words[2] = "2";
hv_words[3] = "1";
hv_words[4] = "3";
hv_words[5] = "0";
hv_words[6] = "A";
hv_words[7] = "0";
hv_words[8] = "4";
hv_words[9] = "0";
hv_words[10] = "6";
hv_words[11] = "2";
hv_words[12] = "0";
GenRectangle1(&ho_ROI_0, 168.5, 16.5, 379.5, 608.5);
TextLineOrientation(ho_ROI_0, ho_Image, 25, -0.523599, 0.523599, &hv_OrientationAngle);
AreaCenter(ho_ROI_0, &hv_Area, &hv_Row, &hv_Column);
VectorAngleToRigid(hv_Row, hv_Column, hv_OrientationAngle, hv_Row, hv_Column, 0,
&hv_HomMat2D);
AffineTransImage(ho_Image, &ho_ImageAffinTrans, hv_HomMat2D, "constant", "false");
//获得点图，点的半径为5，偏移量为2，感兴趣点为黑色点
DotsImage(ho_ImageAffinTrans, &ho_DotImage, 5, "dark", 2);
GenRectangle1(&ho_ROI_0, 195.5, 14.5, 355.5, 612.5);
ReduceDomain(ho_DotImage, ho_ROI_0, &ho_ImageReduced);
Threshold(ho_ImageReduced, &ho_Regions, 20, 255);
//形态学运算
GenRectangle2(&ho_Rectangle1, 0, 0, HTuple(45).TupleRad(), 8, 4);
Closing(ho_Regions, ho_Rectangle1, &ho_RegionClosing);
GenRectangle2(&ho_Rectangle2, 0, 0, HTuple(145).TupleRad(), 8, 4);
Closing(ho_RegionClosing, ho_Rectangle2, &ho_RegionClosing);
DilationCircle(ho_RegionClosing, &ho_RegionDilation1, 4.5);
Connection(ho_RegionDilation1, &ho_ConnectedRegions);
SelectShape(ho_ConnectedRegions, &ho_SelectedRegions, "area", "and", 985.32, 2000.01);
//动态分割
PartitionDynamic(ho_SelectedRegions, &ho_Partitioned, 60, 20);
SortRegion(ho_Partitioned, &ho_SortedRegions, "character", "true", "row");
CountObj(ho_SortedRegions, &hv_Number);
//创建trf训练文件
{
HTuple end_val34 = hv_Number;
HTuple step_val34 = 1;
for (hv_i = 1; hv_i.Continue(end_val34, step_val34); hv_i += step_val34)
{
SelectObj(ho_SortedRegions, &ho_ObjectSelected, hv_i);
//区域和区域作交集
Intersection(ho_ObjectSelected, ho_Regions, &ho_RegionIntersection);
AppendOcrTrainf(ho_RegionIntersection, ho_ImageAffinTrans, HTuple(hv_words[hv_i - 1]),
"C://Users//Administrator//Desktop/halcon//第九讲、halcon联合vc实现ocr识别//train_ocr");
//disp_continue_message (WindowHandle, 'black', 'true')
//stop ()
}
}
ReadOcrTrainfNames("C://Users//Administrator//Desktop/halcon//第九讲、halcon联合vc实现ocr识别//train_ocr",
&hv_CharacterNames, &hv_CharacterCount);
CreateOcrClassMlp(8, 10, "constant", "default", hv_CharacterNames, 80, "none",
10, 42, &hv_OCRHandle);
TrainfOcrClassMlp(hv_OCRHandle, "C://Users//Administrator//Desktop/halcon//第九讲、halcon联合vc实现ocr识别//train_ocr.trf",
200, 1, 0.01, &hv_Error, &hv_ErrorLog);
//也可直接读入halcon训练好的模型文件，则上面的创建训练文件、分类器以及训练都可以不要了
//read_ocr_class_mlp ('Industrial_0-9A-Z_NoRej.omc', OCRHandle)
Intersection(ho_SortedRegions, ho_Regions, &ho_RegionIntersection1);
DoOcrMultiClassMlp(ho_RegionIntersection1, ho_ImageAffinTrans, hv_OCRHandle, &hv_Class,
&hv_Confidence);
SmallestRectangle1(ho_RegionIntersection1, &hv_Row1, &hv_Column1, &hv_Row2, &hv_Column2);
set_display_font(hv_WindowHandle, 26, "mono", "true", "false");
if (HDevWindowStack::IsOpen())
DispObj(ho_ImageAffinTrans, HDevWindowStack::GetActive());
{
HTuple end_val54 = hv_Number - 1;
HTuple step_val54 = 1;
for (hv_j = 0; hv_j.Continue(end_val54, step_val54); hv_j += step_val54)
{
disp_message(hv_WindowHandle, HTuple(hv_Class[hv_j]), "image", HTuple(hv_Row1[hv_j]) + 120,
HTuple(hv_Column1[hv_j]), "white", "false");
//【***】强制转换成字符串类型
CString str = (CString)hv_Class[hv_j].S();
result = result + str;
}
}
//【***】将结果呈现出来
UpdateData(FALSE);
}
运行结果如下：
点击ocr采集识别按钮后结果如下：
