cooc_feature_image ( Regions, Image : : LdGray, Direction : Energy, Correlation, Homogeneity, Contrast )
Calculate a co-occurrence matrix and derive gray value features thereof.
The call of cooc_feature_image corresponds to the consecutive
execution of the operators gen_cooc_matrix and
cooc_feature_matrix. If several direction matrices of the
co-occurrence matrix are to be evaluated consecutively, it is more
efficient to generate the matrix via gen_cooc_matrix and
then call the operator cooc_feature_matrix for the resulting
matrix. The parameter Direction transfers the direction
of the neighborhood in angle or 'mean'. In the case of
'mean' the mean value is calculated in all four
directions.
Parameters
Regions (input_object)
|
region(-array) -> object
|
|
Region to be examined. |
Image (input_object)
|
image -> object : byte
|
|
Corresponding gray values. |
LdGray (input_control)
|
integer -> integer
|
|
Number of gray values to be distinguished
(2^LdGray). |
|
Default value: 6 |
|
List of values: 1, 2, 3, 4, 5, 6, 7, 8 |
Direction (input_control)
|
integer -> integer / string
|
|
Direction in which the matrix is to be calculated. |
|
Default value: 0 |
|
List of values: 0, 45, 90, 135, 'mean' |
Energy (output_control)
|
real(-array) -> real
|
|
Gray value energy. |
Correlation (output_control)
|
real(-array) -> real
|
|
Correlation of gray values. |
Homogeneity (output_control)
|
real(-array) -> real
|
|
Local homogeneity of gray values. |
Contrast (output_control)
|
real(-array) -> real
|
|
Gray value contrast. |
Result
The operator cooc_feature_image returns the value 2 (H_MSG_TRUE) if an
image with defined gray values (byte) is entered and the
parameters are correct. The behavior in case of empty input (no
input images available) is set via the operator
set_system(::'no_object_result',<Result>:), the behavior
in case of empty region is set via
set_system(::'empty_region_result',<Result>:). If
necessary an exception handling is raised.
Parallelization Information
cooc_feature_image is reentrant and automatically parallelized (on tuple level).
Possible Predecessors
gen_cooc_matrix
Alternatives
cooc_feature_matrix
See also
intensity,
min_max_gray,
entropy_gray,
select_gray
Module
Foundation
Copyright © 1996-2008 MVTec Software GmbH