saddle_points_sub_pix — 图像中鞍点的亚像素精度检测。
saddle_points_sub_pix extracts saddle points from the image
Image with subpixel precision, i.e.,
points where along one direction the image intensity is minimal while at the
same time along a different direction the image intensity is maximal.
To do so, in each point the input image is approximated by a quadratic
polynomial in x and y and subsequently the polynomial is examined for
saddle points. The partial derivatives, which are
necessary for setting up the polynomial, are calculated either with various
Gaussian derivatives or using the facet model, depending on Filter.
In the first case, Sigma determines the size of the Gaussian
kernels, while in the second case, before being processed the input image is
smoothed by a Gaussian whose size is determined by Sigma.
Therefore, 'facet' results in a faster extraction at the expense
of slightly less accurate results. A point
is accepted to be a saddle point if the absolute values of both
eigenvalues of the Hessian matrix are greater than Threshold but
their signs differ. The eigenvalues correspond to the curvature of the gray
value surface.
saddle_points_sub_pix is especially useful for the detection of
corners, where fields of different intensity join together like the black
and white fields of a chess board. Their high contrast and shape facilitate
the location and the determination of the precise position of such corners.
请注意，若使用域缩减后的图像作为输入，滤波器算子可能会返回意外结果。请参阅 滤波器 一章
Image (输入对象) singlechannelimage → object (byte / int1 / int2 / uint2 / int4 / real)
输入图像。
Filter (输入控制) string → (string)
Method for the calculation of the partial derivatives.
默认值： 'facet'
值列表： 'facet', 'gauss'
Sigma (输入控制) real → (real)
Sigma of the Gaussian.
If Filter is 'facet', Sigma may be 0.0
to avoid the smoothing of the input image.
建议值： 0.7, 0.8, 0.9, 1.0, 1.2, 1.5, 2.0, 3.0
限制：
Sigma >= 0.0
Threshold (输入控制) real → (real)
Minimum absolute value of the eigenvalues of the Hessian matrix.
默认值： 5.0
建议值： 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0
限制：
Threshold >= 0.0
Row (输出控制) point.y-array → (real)
Row coordinates of the detected saddle points.
Column (输出控制) point.x-array → (real)
Column coordinates of the detected saddle points.
saddle_points_sub_pix returns 2 (
H_MSG_TRUE)
if all parameters are correct
and no error occurs during the execution. 如果输入为空则可设置行为通过 set_system('no_object_result',<Result>)。如有必要，则抛出异常。
gen_cross_contour_xld,
disp_cross
critical_points_sub_pix,
local_min_sub_pix,
local_max_sub_pix
基础