classify_image_class_gmmclassify_image_class_gmmClassifyImageClassGmmClassifyImageClassGmm (Operator)

Name

classify_image_class_gmmclassify_image_class_gmmClassifyImageClassGmmClassifyImageClassGmm — Classify an image with a Gaussian Mixture Model.

Signature

classify_image_class_gmm(Image : ClassRegions : GMMHandle, RejectionThreshold : )

Description

classify_image_class_gmmclassify_image_class_gmmClassifyImageClassGmmClassifyImageClassGmmClassifyImageClassGmm performs a pixel classification with the Gaussian Mixture Model (GMM) GMMHandleGMMHandleGMMHandleGMMHandleGMMHandle on the multichannel image ImageImageImageImageimage. Before calling classify_image_class_gmmclassify_image_class_gmmClassifyImageClassGmmClassifyImageClassGmmClassifyImageClassGmm the GMM must be trained with train_class_gmmtrain_class_gmmTrainClassGmmTrainClassGmmTrainClassGmm. ImageImageImageImageimage must have NumDimNumDimNumDimNumDimnumDim channels, as specified with create_class_gmmcreate_class_gmmCreateClassGmmCreateClassGmmCreateClassGmm. On output, ClassRegionsClassRegionsClassRegionsClassRegionsclassRegions contains NumClassesNumClassesNumClassesNumClassesnumClasses regions as the result of the classification. Note that the order of the regions that are returned in ClassRegionsClassRegionsClassRegionsClassRegionsclassRegions corresponds to the order of the classes as defined by the training regions in add_samples_image_class_gmmadd_samples_image_class_gmmAddSamplesImageClassGmmAddSamplesImageClassGmmAddSamplesImageClassGmm. The parameter RejectionThresholdRejectionThresholdRejectionThresholdRejectionThresholdrejectionThreshold can be used to reject pixels that have an uncertain classification. RejectionThresholdRejectionThresholdRejectionThresholdRejectionThresholdrejectionThreshold represents a threshold on the K-sigma probability measure returned by the classification (see classify_class_gmmclassify_class_gmmClassifyClassGmmClassifyClassGmmClassifyClassGmm and evaluate_class_gmmevaluate_class_gmmEvaluateClassGmmEvaluateClassGmmEvaluateClassGmm). All pixels having a probability below RejectionThresholdRejectionThresholdRejectionThresholdRejectionThresholdrejectionThreshold are not assigned to any class.

Execution Information

Multithreading type: reentrant (runs in parallel with non-exclusive operators).
Multithreading scope: global (may be called from any thread).
Automatically parallelized on internal data level.

Parameters

ImageImageImageImageimage (input_object) (multichannel-)image → object (byte / cyclic / direction / int1 / int2 / uint2 / int4 / real)

Input image.

ClassRegionsClassRegionsClassRegionsClassRegionsclassRegions (output_object) region-array → object

Segmented classes.

GMMHandleGMMHandleGMMHandleGMMHandleGMMHandle (input_control) class_gmm → (integer)

GMM handle.

RejectionThresholdRejectionThresholdRejectionThresholdRejectionThresholdrejectionThreshold (input_control) real → (real)

Threshold for the rejection of the classification.

Default value: 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

Example (HDevelop)

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)
clear_class_gmm (GMMHandle)

If the parameters are valid, the operator classify_image_class_gmmclassify_image_class_gmmClassifyImageClassGmmClassifyImageClassGmmClassifyImageClassGmm returns the value 2 (H_MSG_TRUE). If necessary an exception is raised.