更新时间2018-05-04 10:33:53
如何联合C#编程实现自动识别程序？
例程代码如下：
dev_close_window ()dev_update_off ()read_image (ImageOrig, 'blister/blister_reference')dev_open_window_fit_image (ImageOrig, 0, 0, -1, -1, WindowHandle)set_display_font (WindowHandle, 14, 'mono', 'true', 'false')dev_set_draw ('margin')dev_set_line_width (3)* * In the first step, we create a pattern to cut out the chambers in the* subsequent blister images easily.threshold (ImageOrig, Region, 90, 255)shape_trans (Region, Blister, 'convex')orientation_region (Blister, Phi)area_center (Blister, Area1, Row, Column)vector_angle_to_rigid (Row, Column, Phi, Row, Column, 0, HomMat2D)affine_trans_image (ImageOrig, Image2, HomMat2D, 'constant', 'false')gen_empty_obj (Chambers)for I := 0 to 4 by 1 Row := 88+I*70 for J := 0 to 2 by 1 Column := 163 + J*150 gen_rectangle2 (Rectangle, Row, Column, 0, 64, 30) concat_obj (Chambers, Rectangle, Chambers) endforendforaffine_trans_region (Blister, Blister, HomMat2D, 'false')difference (Blister, Chambers, Pattern)union1 (Chambers, ChambersUnion)orientation_region (Blister, PhiRef)PhiRef := rad(180)+PhiRefarea_center (Blister, Area2, RowRef, ColumnRef)* * * Each image read will be aligned to this pattern and reduced to the area of interest,* which is the chambers of the blisterCount := 6for Index := 1 to Count by 1 read_image (Image, 'blister/blister_'+Index$'02') threshold (Image, Region, 90, 255) connection (Region, ConnectedRegions) select_shape (ConnectedRegions, SelectedRegions, 'area', 'and', 5000, 9999999) shape_trans (SelectedRegions, RegionTrans, 'convex') * * align pattern along blister of image orientation_region (RegionTrans, Phi) area_center (RegionTrans, Area3, Row, Column) vector_angle_to_rigid (Row, Column, Phi, RowRef, ColumnRef, PhiRef, HomMat2D) affine_trans_image (Image, ImageAffinTrans, HomMat2D, 'constant', 'false') * * segment pills reduce_domain (ImageAffinTrans, ChambersUnion, ImageReduced) *进行颜色分开 利用颜色进行筛选 decompose3 (ImageReduced, ImageR, ImageG, ImageB) var_threshold (ImageB, Region, 7, 7, 0.2, 2, 'dark') connection (Region, ConnectedRegions0) closing_rectangle1 (ConnectedRegions0, ConnectedRegions, 3, 3) fill_up (ConnectedRegions, RegionFillUp) select_shape (RegionFillUp, SelectedRegions, 'area', 'and', 1000, 99999) opening_circle (SelectedRegions, RegionOpening, 4.5) connection (RegionOpening, ConnectedRegions) select_shape (ConnectedRegions, SelectedRegions, 'area', 'and', 1000, 99999) shape_trans (SelectedRegions, Pills, 'convex') * * classify segmentation results and display statistics count_obj (Chambers, Number) gen_empty_obj (WrongPill) gen_empty_obj (MissingPill) for I := 1 to Number by 1 select_obj (Chambers, Chamber, I) intersection (Chamber, Pills, Pill) area_center (Pill, Area, Row1, Column1) if (Area > 0) min_max_gray (Pill, ImageB, 0, Min, Max, Range) if (Area<3800 or Min < 60) concat_obj (WrongPill, Pill, WrongPill) endif else concat_obj (MissingPill, Chamber, MissingPill) endif endfor * dev_clear_window () dev_display (ImageAffinTrans) dev_set_color ('forest green') count_obj (Pills, NumberP) count_obj (WrongPill, NumberWP) count_obj (MissingPill, NumberMP) dev_display (Pills) if (NumberMP > 0 or NumberWP > 0) disp_message (WindowHandle, 'Not OK', 'window', 10, 10+600, 'red', 'true') else disp_message (WindowHandle, 'OK', 'window', 10, 10+600, 'forest green', 'true') endif disp_message (WindowHandle, '# correct pills: ' + (NumberP - NumberWP), 'window', 10, 10, 'black', 'true') disp_message (WindowHandle, '# wrong pills : ' + NumberWP, 'window', 10+25, 10, 'black', 'true') if (NumberWP>0) disp_message (WindowHandle, NumberWP, 'window', 10+25, 10+180, 'red', 'true') endif disp_message (WindowHandle, '# missing pills: ' + NumberMP, 'window', 10+50, 10, 'black', 'true') if (NumberMP > 0) disp_message (WindowHandle, NumberMP, 'window', 10+50, 10+180, 'red', 'true') endif dev_set_color ('red') dev_display (WrongPill) dev_display (MissingPill) if (Index < Count) disp_continue_message (WindowHandle, 'black', 'true') endif stop ()endfor
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