halcon 皮革纹理表面缺陷检测

*获取图像大小
get_image_size (Image, Width, Height)
*将图像转化为频域图像
rft_generic (Image, ImageFFT, 'to_freq', 'none', 'complex', Width)
*生成一个高斯滤波核
gen_gauss_filter (ImageGauss, 50, 50, 0, 'n', 'rft', Width, Height)
*将频域图像核高斯滤波核进行卷积运算
convol_fft (ImageFFT, ImageGauss, ImageConvol)
*将卷积后的图像转换为空间域图像
rft_generic (ImageConvol, IlluminationImage, 'from_freq', 'none', 'byte', Width)
return ()
 
 
 
 
* select_mask_obj selects one or more single elements of the object array
* Objects and returns them in SelectedObjects.
* The elements of Mask determine if the corresponding elements of Objects are selected.
* If the value is greater than 0, the corresponding element is selected.
* 
* Check number of elements
count_obj (Objects, Number)
if (Number != |Mask|)
    throw ('Number of elements in Objects and Mask do not match.')
endif
* 
* Check type of mask elements
AllNumbers := sum(is_real_elem(Mask)) + sum(is_int_elem(Mask)) == |Mask|
if (not AllNumbers and Mask != [])
    throw ('Invalid type: Elements of Mask must be integer or real numbers.')
endif
* 
* Use select_mask for tuples to generate a list of object indices.
Indices := select_mask([1:|Mask|],Mask)
select_obj (Objects, SelectedObjects, Indices)
return ()

* 关闭窗口
dev_close_window ()
 
*关闭程序计数器,图形变量,窗口图形更新
dev_update_off ()
 
*图像路径
Path := 'lcd/mura_defects_texture_'
 
*读取一张图像
read_image (Image, Path + '01')
 
*获取图像大小
get_image_size (Image, Width, Height)
 
*打开一个新窗口
dev_open_window (0, 0, 640, 480, 'black', WindowHandle)
 
*设置字体信息:字体大小为16，字体为mono,粗体，斜体
set_display_font (WindowHandle, 14, 'mono', 'true', 'false')
 
*设置区域的填充方式
dev_set_draw ('margin')
 
*设置线宽度
dev_set_line_width (3)
 
*设置输出对象显示颜色
dev_set_color ('red')
 
 
for F := 1 to 2 by 1
    
    read_image (Image, Path + F$'.2i')
    
    *获取彩色图像的三个通道,R,G,B
    decompose3 (Image, R, G, B)
    
    *缺陷是暗斑。 因此，通过原始图像减去背景照明，从而使缺陷变得更加明显。
    estimate_background_illumination (B, ImageFFT1)
    
    *用缺陷图减去背景图
    sub_image (B, ImageFFT1, ImageSub, 2, 100)
    
    *中值滤波
    median_image (ImageSub, ImageMedian, 'circle', 9, 'mirrored')
    
    *提取分水岭盆地
    watersheds_threshold (ImageMedian, Basins, 20)
    
    *计算灰度共生矩阵的灰度值特性,暗斑的能量非常低
    cooc_feature_image (Basins, ImageMedian, 6, 0, Energy, Correlation, Homogeneity, Contrast)
    *Energy小于0.05，Mask为1，否则为0
    Mask := Energy [<=] 0.05
    select_mask_obj (Basins, Defects, Mask)
    
    * 显示图像
    dev_display (Image)
    
    * 显示缺陷
    dev_display (Defects)
    
    stop()
    
endfor