一、检测目的
由于一次很难将一个产品拍全，所以我们要多次拍照，然后让图片拼接成一张图。
二、原图
image.png
image.png
image.png
三、代码实现
dev_update_off ()
dev_close_window ()
dev_open_window (0, 0, 500, 500, 'white', WindowHandle)
dev_set_color ('green')
set_display_font (WindowHandle, 14, 'mono', 'true', 'false')
*创建一个空的对象元组
gen_empty_obj (Images)
*遍历文件夹图像
iImgNum:=3
ImageFiles:='Image2/'
for J := 1 to iImgNum by 1
read_image (Image, 'Image2/'+J+'.bmp')
concat_obj (Images, Image, Images)
dev_display (Image)
disp_message (WindowHandle, 'Image ' + J$'d', 'image', -1, -1, 'black', 'true')
wait_seconds (1)
endfor
*更改活动图形窗口的位置和大小
dev_set_window_extents (-1, -1, 1000/3 ,4600/3 )
*将多个图像对象平铺到具有显式定位信息的大图像中
tile_images_offset (Images, TiledImage, [0,1000,2000], [0,0,0], [-1,-1,-1], [-1,-1,-1], [-1,-1,-1], [-1,-1,-1], 3000,4600)
dev_clear_window ()
dev_display (TiledImage)
stop ()
dev_clear_window ()
dev_display (TiledImage)
disp_message (WindowHandle, 'Point matches', 'window', 12, 3, 'black', 'true')
*定义图像对，即哪个图像应该映射到哪个图像。
From := [1,2]
To := [2,3]
Num := |From|
*一个变量来积累投影变换矩阵。
ProjMatrices := []
*此外，由于我们要在下面创建精确镶嵌，所以我们需要积累所有对应的点和每个图像对的匹配数。
Rows1 := []
Cols1 := []
Rows2 := []
Cols2 := []
NumMatches := []
for J := 0 to Num - 1 by 1
F := From[J]
T := To[J]
select_obj (Images, ImageF, F)
select_obj (Images, ImageT, T)
points_foerstner (ImageF, 1, 2, 3, 200, 0.3, 'gauss', 'false', RowJunctionsF, ColJunctionsF, CoRRJunctionsF, CoRCJunctionsF, CoCCJunctionsF, RowAreaF, ColAreaF, CoRRAreaF, CoRCAreaF, CoCCAreaF)
points_foerstner (ImageT, 1, 2, 3, 200, 0.3, 'gauss', 'false', RowJunctionsT, ColJunctionsT, CoRRJunctionsT, CoRCJunctionsT, CoCCJunctionsT, RowAreaT, ColAreaT, CoRRAreaT, CoRCAreaT, CoCCAreaT)
*通过查找点之间的对应关系，计算两个图像之间的投影变换矩阵。
proj_match_points_ransac (ImageF, ImageT, RowJunctionsF, ColJunctionsF, RowJunctionsT, ColJunctionsT, 'ncc', 21, 0, 0, 1000, 1000, 0, 0.5, 'gold_standard', 1, 4364537, ProjMatrix, Points1, Points2)
* Accumulate the transformation matrix.
ProjMatrices := [ProjMatrices,ProjMatrix]
* Accumulate the point matches and number of point matches.
Rows1 := [Rows1,subset(RowJunctionsF,Points1)]
Cols1 := [Cols1,subset(ColJunctionsF,Points1)]
Rows2 := [Rows2,subset(RowJunctionsT,Points2)]
Cols2 := [Cols2,subset(ColJunctionsT,Points2)]
NumMatches := [NumMatches,|Points1|]
* Generate crosses that represent the extracted points in the tiled image.
* Note that we have to take the row offsets of the images in the tiled image
* into account.
*生成表示平铺图像中提取点的十字。 请注意，我们必须考虑平铺图像中的图像的行偏移量。
*参数1：生成XLD轮廓。
*参数2,3：输入点的行、列坐标
*参数4：横杠的长度。
*参数5：取向的十字架。
gen_cross_contour_xld (PointsF, RowJunctionsF + (F - 1) * 1000, ColJunctionsF, 6, rad(45))
gen_cross_contour_xld (PointsT, RowJunctionsT + (T - 1) * 1000, ColJunctionsT, 6, rad(45))
* Generate a representation of the matched point pairs as lines. We create
* XLD contours from the lines so that we can zoom into the graphics window
* to take a closer look at the matches.
*生成匹配点对的表示为行。 我们从行中创建XLD轮廓，
*以便我们可以放大图形窗口，以便仔细观察匹配。
*t := subset(t,i) 选取数组t中的第i个元素
RowF := subset(RowJunctionsF,Points1) + (F - 1) * 1000
ColF := subset(ColJunctionsF,Points1)
RowT := subset(RowJunctionsT,Points2) + (T - 1) * 1000
ColT := subset(ColJunctionsT,Points2)
gen_empty_obj (Matches)
for K := 0 to |RowF| - 1 by 1
*从多边形（给定为元组）生成XLD轮廓。
gen_contour_polygon_xld (Match, [RowF[K],RowT[K]], [ColF[K],ColT[K]])
*连接两个标志性的对象元组。
concat_obj (Matches, Match, Matches)
endfor
* Now display the extracted data.现在显示所提取的数据。
dev_set_color ('blue')
dev_display (Matches)
dev_set_color ('green')
dev_display (PointsF)
dev_display (PointsT)
endfor
stop ()
*最后，我们可以从投影变换生成马赛克图像。
*将多个图像合并成一个镶嵌图像。
gen_projective_mosaic (Images, MosaicImage, 2, From, To, ProjMatrices, 'default', 'false', MosaicMatrices2D)
get_image_size (MosaicImage, Width, Height)
*改变活动图形窗口的位置和大小。
dev_set_window_extents (-1, -1, Width / 3, Height / 3)
dev_clear_window ()
dev_display (MosaicImage)
disp_message (WindowHandle, 'Projective mosaic', 'window', 12, 12, 'black', 'true')
disp_message (WindowHandle, 'Click \'Run\'\nto continue', 'window', Height / 3 - 50, 12, 'black', 'true')
stop ()
*为了更清楚地显示图像中可见的折叠不是由镶嵌形成的，
*我们将显示镶嵌图像中的图像之间的接缝。 这可以通过创建包含图像边框的图像，
*从中生成镶嵌并分割生成的镶嵌图像来最容易地完成。
get_image_size (Image, Width, Height)
*创建一个具有恒定灰度值的图像。
gen_image_const (ImageBlank, 'byte', Width, Height)
gen_rectangle1 (Rectangle, 0, 0, Height - 1, Width - 1)
*把区域涂成图像。
paint_region (Rectangle, ImageBlank, ImageBorder, 255, 'margin')
gen_empty_obj (ImagesBorder)
for J := 1 to iImgNum by 1
concat_obj (ImagesBorder, ImageBorder, ImagesBorder)
endfor
gen_projective_mosaic (ImagesBorder, MosaicImageBorder, 2, From, To, ProjMatrices, 'default', 'false', MosaicMatrices2D)
threshold (MosaicImageBorder, Seams, 128, 255)
dev_clear_window ()
dev_display (MosaicImage)//Seams接缝
disp_message (WindowHandle, '各图像间的接缝', 'window', 12, 12, 'black', 'true')
dev_set_color ('yellow')
dev_display (Seams)
disp_message (WindowHandle, 'Click \'Run\'\nto continue', 'window', 550, 12, 'black', 'true')
*将窗口内容写入文件
dump_window (WindowHandle, 'bmp', ImageFiles+'拼接缝截图')
stop ()
*对图像马赛克进行捆绑调整。
bundle_adjust_mosaic (iImgNum, 1, From, To, ProjMatrices, Rows1, Cols1, Rows2, Cols2, NumMatches, 'rigid', MosaicMatrices2D, Rows, Cols, Error)
* Now, we can generate the mosaic image from the rigid transformations.
*现在，我们可以通过精确变换生成马赛克图像。
gen_bundle_adjusted_mosaic (Images, MosaicImageRigid, MosaicMatrices2D, 'default', 'false', TransMatrix2D)
get_image_size (MosaicImageRigid, Width, Height)
dev_set_window_extents (-1, -1, Width / 3, Height / 3)
dev_clear_window ()
dev_display (MosaicImageRigid)
disp_message (WindowHandle, '精确拼接图', 'window', 12, 12, 'black', 'true')
dump_window (WindowHandle, 'bmp', ImageFiles+'精确拼接截图')
运行结果：
image.png
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