classify_image_class_gmmT_classify_image_class_gmmClassifyImageClassGmmClassifyImageClassGmmclassify_image_class_gmm (Operator)
Name
classify_image_class_gmmT_classify_image_class_gmmClassifyImageClassGmmClassifyImageClassGmmclassify_image_class_gmm — Classify an image with a Gaussian Mixture Model.
Signature
Description
classify_image_class_gmmclassify_image_class_gmmClassifyImageClassGmmClassifyImageClassGmmClassifyImageClassGmmclassify_image_class_gmm performs a pixel classification
with the Gaussian Mixture Model (GMM) GMMHandleGMMHandleGMMHandleGMMHandleGMMHandlegmmhandle on the
multichannel image ImageImageImageImageimageimage. Before calling
classify_image_class_gmmclassify_image_class_gmmClassifyImageClassGmmClassifyImageClassGmmClassifyImageClassGmmclassify_image_class_gmm the GMM must be trained with
train_class_gmmtrain_class_gmmTrainClassGmmTrainClassGmmTrainClassGmmtrain_class_gmm. ImageImageImageImageimageimage must have NumDimNumDimNumDimNumDimnumDimnum_dim
channels, as specified with create_class_gmmcreate_class_gmmCreateClassGmmCreateClassGmmCreateClassGmmcreate_class_gmm. On output,
ClassRegionsClassRegionsClassRegionsClassRegionsclassRegionsclass_regions contains NumClassesNumClassesNumClassesNumClassesnumClassesnum_classes regions as the
result of the classification. Note
that the order of the regions that are returned in
ClassRegionsClassRegionsClassRegionsClassRegionsclassRegionsclass_regions corresponds to the order of the classes as
defined by the training regions in
add_samples_image_class_gmmadd_samples_image_class_gmmAddSamplesImageClassGmmAddSamplesImageClassGmmAddSamplesImageClassGmmadd_samples_image_class_gmm. The parameter
RejectionThresholdRejectionThresholdRejectionThresholdRejectionThresholdrejectionThresholdrejection_threshold can be used to reject pixels that have
an uncertain classification. RejectionThresholdRejectionThresholdRejectionThresholdRejectionThresholdrejectionThresholdrejection_threshold represents
a threshold on the K-sigma probability measure returned by the
classification (see classify_class_gmmclassify_class_gmmClassifyClassGmmClassifyClassGmmClassifyClassGmmclassify_class_gmm and
evaluate_class_gmmevaluate_class_gmmEvaluateClassGmmEvaluateClassGmmEvaluateClassGmmevaluate_class_gmm). All pixels having a probability below
RejectionThresholdRejectionThresholdRejectionThresholdRejectionThresholdrejectionThresholdrejection_threshold 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
ImageImageImageImageimageimage (input_object) (multichannel-)image → objectHImageHObjectHImageHobject (byte / cyclic / direction / int1 / int2 / uint2 / int4 / real)
Input image.
ClassRegionsClassRegionsClassRegionsClassRegionsclassRegionsclass_regions (output_object) region-array → objectHRegionHObjectHRegionHobject *
Segmented classes.
GMMHandleGMMHandleGMMHandleGMMHandleGMMHandlegmmhandle (input_control) class_gmm → HClassGmm, HTupleHHandleHTupleHtuple (handle) (IntPtr) (HHandle) (handle)
GMM handle.
RejectionThresholdRejectionThresholdRejectionThresholdRejectionThresholdrejectionThresholdrejection_threshold (input_control) real → HTuplefloatHTupleHtuple (real) (double) (double) (double)
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)
Result
If the parameters are valid, the operator
classify_image_class_gmmclassify_image_class_gmmClassifyImageClassGmmClassifyImageClassGmmClassifyImageClassGmmclassify_image_class_gmm returns the value 2 (H_MSG_TRUE). If
necessary an exception is raised.
Possible Predecessors
train_class_gmmtrain_class_gmmTrainClassGmmTrainClassGmmTrainClassGmmtrain_class_gmm,
read_class_gmmread_class_gmmReadClassGmmReadClassGmmReadClassGmmread_class_gmm
Alternatives
classify_image_class_knnclassify_image_class_knnClassifyImageClassKnnClassifyImageClassKnnClassifyImageClassKnnclassify_image_class_knn,
classify_image_class_mlpclassify_image_class_mlpClassifyImageClassMlpClassifyImageClassMlpClassifyImageClassMlpclassify_image_class_mlp,
classify_image_class_svmclassify_image_class_svmClassifyImageClassSvmClassifyImageClassSvmClassifyImageClassSvmclassify_image_class_svm,
classify_image_class_lutclassify_image_class_lutClassifyImageClassLutClassifyImageClassLutClassifyImageClassLutclassify_image_class_lut,
class_ndim_normclass_ndim_normClassNdimNormClassNdimNormClassNdimNormclass_ndim_norm,
class_2dim_supclass_2dim_supClass2dimSupClass2dimSupClass2dimSupclass_2dim_sup
See also
add_samples_image_class_gmmadd_samples_image_class_gmmAddSamplesImageClassGmmAddSamplesImageClassGmmAddSamplesImageClassGmmadd_samples_image_class_gmm,
create_class_gmmcreate_class_gmmCreateClassGmmCreateClassGmmCreateClassGmmcreate_class_gmm
Module
Foundation