classify_image_class_gmm — Classify an image with a Gaussian Mixture Model.
classify_image_class_gmm(Image : ClassRegions : GMMHandle, RejectionThreshold : )
classify_image_class_gmm performs a pixel classification
with the Gaussian Mixture Model (GMM) GMMHandle on the
multichannel image Image. Before calling
classify_image_class_gmm the GMM must be trained with
train_class_gmm. Image must have NumDim
channels, as specified with create_class_gmm. On output,
ClassRegions contains NumClasses regions as the
result of the classification. Note
that the order of the regions that are returned in
ClassRegions corresponds to the order of the classes as
defined by the training regions in
add_samples_image_class_gmm. The parameter
RejectionThreshold can be used to reject pixels that have
an uncertain classification. RejectionThreshold represents
a threshold on the K-sigma probability measure returned by the
classification (see classify_class_gmm and
evaluate_class_gmm). All pixels having a probability below
RejectionThreshold are not assigned to any class.
Image (input_object) (multichannel-)image → object (byte / cyclic / direction / int1 / int2 / uint2 / int4 / real)
Input image.
ClassRegions (output_object) region-array → object
Segmented classes.
GMMHandle (input_control) class_gmm → (handle)
GMM handle.
RejectionThreshold (input_control) real → (real)
Threshold for the rejection of the classification.
Default: 0.5
Suggested values: 0.0, 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1.0
Restriction:
RejectionThreshold >= 0.0 && RejectionThreshold <= 1.0
read_image (Image, 'ic') gen_rectangle1 (Board, 80, 320, 110, 350) gen_rectangle1 (Capacitor, 359, 263, 371, 302) gen_rectangle1 (Resistor, 200, 252, 290, 256) gen_rectangle1 (IC, 180, 135, 216, 165) concat_obj (Board, Capacitor, Classes) concat_obj (Classes, Resistor, Classes) concat_obj (Classes, IC, Classes) create_class_gmm (3, 4, [1,30], 'full', 'none',0, 42, GMMHandle) add_samples_image_class_gmm (Image, Classes, GMMHandle, 1.5) get_sample_num_class_gmm (GMMHandle, NumSamples) train_class_gmm (GMMHandle, 150, 1e-4, 'training', 1e-4, Centers, Iter) classify_image_class_gmm (Image, ClassRegions, GMMHandle, 0.0001)
If the parameters are valid, the operator
classify_image_class_gmm returns the value 2 (
H_MSG_TRUE)
. If
necessary an exception is raised.
train_class_gmm,
read_class_gmm
classify_image_class_knn,
classify_image_class_mlp,
classify_image_class_svm,
classify_image_class_lut,
class_ndim_norm,
class_2dim_sup
add_samples_image_class_gmm,
create_class_gmm
Foundation