机器视觉Halcon检测动态想要的特征区域识别字符

光学字符识别是机器视觉领域非常重要的一个应用。机器视觉是集光学、机电和计算机三个领域的一门不算新的技术。此例子用的CNN神经网络算子识别，调用的训练库是系统HDevelop自带的
识别的图片为电表的屏幕截图，用于提取电表中间的一大串数字
要识别的图片：

识别过程
1、阈值处理
mean_image(Image,Mean,15,15)
dyn_threshold(Image,Mean,Region,5,‘dark’)
dev_display (Region)
图片效果：

2、执行代码：
*连接字符
closing_rectangle1 (Region, RegionClosing1, 1, 5)

3、裁剪不要的，将不要的其他区域剪小
opening_circle (RegionClosing1, GuoRegion,2.2)

4、 *筛选区域
在调用select_shape 之前必须要调用连通区域方法connection 才有效果，切记
*计算区域的连通组件
connection (GuoRegion, ConnPatterns)

5、筛选区域
select_shape (ConnPatterns, shapeRegion, ‘area’, ‘and’, 260, 99999)

6、去掉头顶的红杠
*去掉图片头顶的红色横杠
select_shape (shapeRegion, shapeRegion2, ‘width’, ‘and’, 10, 100)

7、求交集，与第一步处理后的区域求交集
*求交集 以区分的颜色模块在前，原字符再后，才能单独著色交集后的单体字符
intersection (shapeRegion2, Region, RegionIntersection)
dev_display(RegionIntersection)

8、最后用cnn卷积神经网络识别
*排序
sort_region (RegionIntersection, SortedRegions, ‘character’, ‘true’, ‘row’)

dev_set_draw (‘margin’)
dev_set_shape (‘rectangle1’)
dev_display (SortedRegions)

shape_trans (SortedRegions, RegionTrans, ‘rectangle1’)
area_center (RegionTrans, Area, Row, Column)
MeanRow := mean(Row)
FontName := ‘Universal_Rej’
count_obj (SortedRegions, Number)
read_ocr_class_cnn (FontName, OCRHandle)
for I := 1 to Number by 1
select_obj (SortedRegions, ObjectSelected, I)
do_ocr_single_class_cnn (ObjectSelected, Image, OCRHandle, 1, Class, Confidence)
dev_disp_text (Class, ‘image’, MeanRow+30, Column[I - 1]-5, ‘green’, ‘box’, ‘false’)
endfor

识别结果：

Halcon HDevelop完整代码：

dev_update_off()
read_image(Image,'d:/Desktop/vision/DBIAO01.png')
get_image_size(Image,Width,Height)

dev_close_window ()
dev_open_window (0, 0, Width*2, Height*2, 'black', WindowHandle)
set_display_font (WindowHandle, 30, 'mono', 'true', 'false')
dev_display (Image)

dev_set_line_width (2)

mean_image(Image,Mean,15,15)
dyn_threshold(Image,Mean,Region,5,'dark')
dev_display (Region)

 *clip_region (Region, RawSegmentation, 74.8873, 58.6812, 132.943, 312.194) 
*select_shape (Region, SelectedRegions, 'height', 'and',170,99999)
*gen_rectangle1 (ROI_0, 73.2924, 55.8125, 135.814, 312.938)

 *连接字符，以9度闭合画圆圈
*closing_circle (CharCandidates, RegionClosing1, 1.5)
closing_rectangle1 (Region, RegionClosing1, 1, 5)
*去除不要的
opening_circle (RegionClosing1, GuoRegion,2.2)

*  fill_up (RegionClosing1, Solid)
* opening_rectangle1 (Solid, Cut, 5, 2)

*计算区域的连通组件
 connection (GuoRegion, ConnPatterns)
 *筛选区域
 select_shape (ConnPatterns, shapeRegion, 'area', 'and', 260, 99999)
 *去掉图片头顶的红色横杠
 select_shape (shapeRegion, shapeRegion2, 'width', 'and', 10, 100)

*求交集 以区分的颜色模块在前，原字符再后，才能单独著色交集后的单体字符
intersection (shapeRegion2, Region, RegionIntersection) 
dev_display(RegionIntersection)

 *排序
sort_region (RegionIntersection, SortedRegions, 'character', 'true', 'row') 

dev_set_draw ('margin')
dev_set_shape ('rectangle1')
dev_display (SortedRegions)

shape_trans (SortedRegions, RegionTrans, 'rectangle1')
area_center (RegionTrans, Area, Row, Column)
MeanRow := mean(Row)
FontName := 'Universal_Rej'
count_obj (SortedRegions, Number)
read_ocr_class_cnn (FontName, OCRHandle)
for I := 1 to Number by 1
    select_obj (SortedRegions, ObjectSelected, I)
    do_ocr_single_class_cnn (ObjectSelected, Image, OCRHandle, 1, Class, Confidence)
    dev_disp_text (Class, 'image', MeanRow+30, Column[I - 1]-5, 'green', 'box', 'false')
endfor