十五.halcon学习之数据结构

Halcon数据结构总结：

    一.两类参数：图形参数Iconic (image, region, XLD)与控制参数Control (string, integer, real, handle)，在Halcon算子的参数中，依次为：输入图形参数、输出图形参数、输入控制参数、输出控制参数；并且其输入参数不会被算子改变。

图形参数Iconic：

1.Images

Halcon中，Image = Channel + Domain , 像素点存放在Channel矩阵中，根据ROI来描述Image。

Image相关操作：

输入：从文件、从设备

生成：外部图像数据、空内存区域；

显示：disp_image()图像首通道灰度图；disp_color() 彩色图；disp_channel()某特定通道；disp_obj() 自动判别类别；

缩放：set_part() 设置显示区域；set_part_style() 设置显示参数；

说明：

（1）Multiple channels    //多通道图像，可以是灰度图像或RGB图像

（2）Arbitrary region of interest //ROI区域图像

（3）Multiple pixel types(byte, (u)int1/2/4,real, complex, direction, cyclic, vector_field)

  byte, uint2        //灰度图像的标准编码

  int1, int2         //Difference of two images or derivates with integer precision    int4                 //两幅灰度图的频谱

direction           //图片边缘的梯度方向

real                //边缘提取及特定灰度值的轮廓

complex            //图片频率

cyclic             //Assigning one "gray" value to each color（？？）

vector_field      //连续图形的光学流分布

2.Regions

以行列坐标形式储存，有广泛的应用，特点是高效，可利用同态算子。比如用阈值对图像分割的结果，其他系统中称为BOLB,AREA等。

3. Extended Line Description (XLD)

图像均用像素点保存，而像素点是整型的，不连续的，Halcon做了拓展，定义了亚像素（subpixel）的描述几何轮廓的对象：xld，主要用在亚像素测量的背景下，可用于如提取边缘、构建轮廓等等，xld在模板匹配、图形校准等多方面有重要的用途。

   Subpixel accurate line and edge detection（亚像素精度的线和边缘检测）

   Generic point list based data structure（依据数据结构产生点的表）

   Handling of contours, polygons, lines, parallels, etc.（对轮廓，多边形，线等进行操作）

   此外，Halcon支持的类型还包括图形元组、控制变量元组及句柄：

元组使得可以用一个变量传递数个对象，可以由重载后的函数来进行处理；图形元组的下标从1开始，控制变量元组下标从0开始；句柄则可以用来描述窗体、文件等等，句柄不能是常量。

二.区域运算：

并：union1()、union2()；

交：intersection();

差：difference();

补：complement()；

图形显示参数设置：

显示模式：set_draw(); 参数：margin、filled

线宽线形：set_line_width(); set_line_style();

颜色：set_color(); set_colored(); set_rgb(); set_gray();

显示图形：set_shape(); 参数：original、outer circle、inner circle、rectangle1、rectangle2、ellipse、icon

set_icon

三.附加重要名词解释 

Domain: Part of the image which is used for processing. In other systems called ROI (region of interest).（待处理的区域）

Channel: One image matrix of a multi-spectral image. One example is the red channel of an RGB image.

Iconic data: Overall term for images, regions, and XLD data. In object oriented languages (C++ and COM) and in HDevelop iconic data is represented by a polymorphic data type. In object oriented languages iconic data is also called iconic object.

Control data: All non iconic data. Examples are single values (integer, real, and string), coordinates, arrays of values.

Tuple: an array of values where each element can be of a different type. One can have both iconic and control tuples.

HALCON object: Synonym for Iconic object / data

Image acquisition interface: Interface between the frame grabber /camera driver (SDK) and the HALCON library. The Image acquisition interface is a DLL which is dynamically loaded when calling open_framegrabber.

Language interface: Software that enables the programmer to use the HALCON library in a given language (e.g., C++).

Extension Package: A mechanism that enables the user to fully integrate user-defined procedures into the HALCON environment. The extension package concept gives full access to the internal data structures of HALCON.

License file: File “license.dat“ in the directory “license“.  This file is used together with hardware components (dongle or Ethernet card) to check if a correct license is available.

Help files: Files in the directory “help“ which are used to get online information about all HALCON operators. This is extensively used by HDevelop.

Shape-Based Matching: Finding of an object in an image based on a predefined model. The shape based matching uses features to quickly locate objects very precisely.

Variation Model: A method to do print checking by presenting multiple good patterns to the system. The variation model learns the normal variation a good pattern and based on this information can detect real defects.

Measure Tool: A set of operators to find the exact location of edges along lines or circular arcs. Other systems call the similar tool, e.g., caliper.

Accuracy: The deviation from the true value（准确性，和真值之间的差）

Precision: The standard deviation of the measurement（精度，测量标准差）