Some uses of Halcon array

halcon Some uses of arrays

There's nothing to talk about , I won't explain things that are not part of the array here .

1. area_center(RegionOpening,Area, Row, Column). Use area_center To find the center and area of a region , return Area, Row, Column These three parameters . When the number of regions is greater than 1 when ,Area, Row, Column It's all an array
   
   Back to Area, Row, Column These three arrays ,Area It is sorted according to the area from small to small ,Row and Column It's corresponding to Area The center of the area , namely Row and Column The first element of is the central coordinate of the area with the smallest area

2. tuple_sort_index(Column,Sorted_Column)： Yes Column Sort （ From small to large ）, The index of the sorted element is returned . for example Column yes 【300,200, 100】, Back to Sorted_Column=【2,1,0】
3. new_row := Row[Sorted_Column]： Give Way Row With Sorted_Column Sort in a different way , Then assign the value to new_row. for example Row=【20, 10, 50】,Sorted_Column=【2,1,0】----->  Row[Sorted_Column]  = 【50,10,20】
4. Halcon The array in can only be 1xN Array of , That is, arrays cannot be nested in an array

read_image(Image, 'printer_chip/printer_chip_01')
* Display images 

* Open a file of size 512,512 The window of 
dev_open_window(0, 0, 512, 512, 'black', WindowHandle)
dev_display(Image)
* Draw a rectangle on the window ROT Area 
draw_rectangle1(WindowHandle, Row1, Column1, Row2, Column2)
* Make rectangle ROI Area 
gen_rectangle1(Rectangle_Roi, Row1, Column1, Row2, Column2)
* Process the pictures , Leave only ROI Image of the area , The rest turned black 
reduce_domain(Image, Rectangle_Roi, ImageReduced)

* Average filter the image ,10,10 yes kernel Size 
mean_image(ImageReduced, ImageMean, 10, 10)
* Calculate the difference between the original image and the image after the average value , If the difference exceeds 5 The retention 
dyn_threshold(ImageReduced, ImageMean, RegionDynThresh, 5, 'dark')
* Break up the area 
connection(RegionDynThresh, ConnectedRegions)
* Use area to filter 
select_shape(ConnectedRegions, SelectedRegions, 'area', 'and', 4000, 99999)
* Fill the area 
fill_up(SelectedRegions, RegionFillUp)
* Use a size of 50*50 To perform the open operation , I can put it down 50*50 The region of the matrix is reserved , Those that cannot be put down will be eliminated 
opening_rectangle1(RegionFillUp, RegionOpening, 50, 50)
* Count the number of areas 
count_obj(RegionOpening, Number)
* Find the center and area of each region , When the number of regions is greater than 1 when ,Area, Row, Column It's all an array 
area_center(RegionOpening,Area, Row, Column)
* Because the areas are all on the same horizontal line , So according to column To sort , From small to large . What is returned is after sorting index Array of 
tuple_sort_index(Column,Sorted_Column)

*halcon Array operations in , Is to put Row and Column The elements of are sorted according to the above sorting method 
new_row := Row[Sorted_Column]
new_column := Column[Sorted_Column]

* Create an array to count the distance between two adjacent areas 
distance_list := []
* Use for Loop to traverse , Calculate the distance between the current area and the next area 
for j := 0 to Number-1 by 1
    * Draw the center of the area 
    gen_circle(Circle, new_row[j], new_column[j], 10)
    * Because the center of each area should be depicted here , therefore j be equal to Number-1 Also draw the center 
    * but j be equal to Number-1 The distance is not calculated , because Number-1 It's the last area , No other area can calculate the distance with him 
    * So use break Out of the loop 
    if (j == Number-1)
       break
    endif
    * Formula for calculating the distance between points ,new_row[j], new_column[j] Is the coordinate of the first point 
    distance_pp(new_row[j], new_column[j], new_row[j+1], new_column[j+1], Distance)
    * Put the distance between two local areas into the array . Explain in halcon Array can only be 1xN Array of , You cannot set an array inside an array 
    distance_list[j] := Distance
endfor