少有人走的路程序调用十张不同光照下的图片，尝试找ncc模板，求取模板位置。最后计算结果的标准差。
代码如下：
* This example program shows how to use HALCON's correlation-based
* matching. In particular it demonstrates the robustness of this method against
* linear illumination changes. The training is performed in an image with good
* illumination. The matching is applied in images where the exposure time varies
* extremely from very short to very long.
read_image (Image, 'cap_exposure/cap_exposure_03')
dev_close_window ()
dev_open_window_fit_image (Image, 0, 0, -1, -1, WindowHandle)
set_display_font (WindowHandle, 16, 'mono', 'true', 'false')
dev_update_off ()
gen_circle (Circle, 246, 336, 150)
area_center (Circle, Area, RowRef, ColumnRef)
reduce_domain (Image, Circle, ImageReduced)
create_ncc_model (ImageReduced, 'auto', 0, 0, 'auto', 'use_polarity', ModelID)
dev_set_draw ('margin')
dev_display (Image)
dev_set_color ('yellow')
dev_display (Circle)
disp_message (WindowHandle, 'Trained NCC model', 'window', 12, 12, 'black', 'true')
disp_continue_message (WindowHandle, 'black', 'true')
stop ()
Rows := []
Cols := []
for J := 1 to 10 by 1
read_image (Image, 'cap_exposure/cap_exposure_' + J$'02')
find_ncc_model (Image, ModelID, 0, 0, 0.5, 1, 0.5, 'true', 0, Row, Column, Angle, Score)
*（1）
* 仿射变换，变换圆的位置
vector_angle_to_rigid(RowRef, ColumnRef, Angle, Row, Column, 0, HomMat2D)
affine_trans_region(Circle, RegionAffineTrans, HomMat2D, 'nearest_neighbor')
Rows := [Rows,Row]
Cols := [Cols,Column]
dev_display (Image)
dev_display(RegionAffineTrans)
*（2）
* 下面这句被注释掉的和（1）的两句功能都是一样的，启用前请先把（1）的两句注释掉
*dev_display_ncc_matching_results (ModelID, 'green', Row, Column, Angle, 0)
disp_message (WindowHandle, 'Found NCC model', 'window', 12, 12, 'black', 'true')
if (J < 10)
disp_continue_message (WindowHandle, 'black', 'true')
endif
stop ()
endfor
*计算十张图找ncc模板后的坐标位置的标准差
StdDevRows := deviation(Rows)
StdDevCols := deviation(Cols)结果如下：
这个差别是相当的小，最大差别0.087个像素。
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