Rockwell Automation 5370-CVIM2 Module - Manual (Page 300)

Chapter 7
Inspection Tools
7–62
The Transform operation is the appropriate choice under the following
conditions:
•
The required image processing can be performed adequately using
morphology filters alone.
•
An “unwrap” or “warp” spatial transformation function is required, and it
can be performed by the arc ring, quad, or perspective shape.
In the first instance, refer to Chapter 8, Thresholds, Filters, and Morphology,
in the Area Tools: Threshold and Morphology Functions section for
morphology details. In the second instance, refer to the Shape section on
page 7–87 of this chapter for details about the “unwrap” and “warp” spatial
transformation functions.
The Convolve operation type is an appropriate choice when the Transform
operation, using morphology filtering, cannot adequately process the image.
In addition to morphology filtering, the Convolve operation provides several
spatial filtering functions, some using kernels with fixed coefficients, that
can clarify or sharpen image features, or can smooth features and/or reduce
noise in the image.
Convolve also provides two kernels having
user–configurable coefficients, for situations in which the fixed–coefficient
kernels do not quite match the spatial filtering requirements. These kernels
enable the user to experiment with other coefficient configurations in an
attempt to improve the feature enhancement results.
This section discusses the details of the various spatial filter functions
performed by the kernels listed in the
Image Kernel selection panel
(Figure 7.75, page 7–91) and illustrates their effects on image features. This
section also provides a selection table that correlates the various kernels with
the LUT(s) that are the most appropriate for the desired feature enhancement
outcomes.
Sobel X, Sobel Y Kernels
The Sobel X and Sobel Y kernels perform directional spatial filtering
functions that sharpen gradients lying along the Y–axis of the image ( Sobel
X ) or the X–axis ( Sobel Y ). The kernels for these two functions use the same
coefficient values, but these values are arrayed differently in each kernel.
Sobel X Kernel –– The coefficients in the Sobel X kernel are arrayed in a
3x3 matrix, as follows:
0 1
2
1
0
0
–1
–2
–1
Image Tool Operations:
Transform
Image Tool Operations:
Convolve