add_samples_image_class_gmmT_add_samples_image_class_gmmAddSamplesImageClassGmmAddSamplesImageClassGmmadd_samples_image_class_gmm (Operator)

Name

add_samples_image_class_gmmT_add_samples_image_class_gmmAddSamplesImageClassGmmAddSamplesImageClassGmmadd_samples_image_class_gmm — Add training samples from an image to the training data of a Gaussian Mixture Model.

Signature

add_samples_image_class_gmm(Image, ClassRegions : : GMMHandle, Randomize : )

Description

add_samples_image_class_gmmadd_samples_image_class_gmmAddSamplesImageClassGmmAddSamplesImageClassGmmAddSamplesImageClassGmmadd_samples_image_class_gmm adds training samples from the ImageImageImageImageimageimage to the Gaussian Mixture Model (GMM) given by GMMHandleGMMHandleGMMHandleGMMHandleGMMHandlegmmhandle. add_samples_image_class_gmmadd_samples_image_class_gmmAddSamplesImageClassGmmAddSamplesImageClassGmmAddSamplesImageClassGmmadd_samples_image_class_gmm is used to store the training samples before a classifier to be used for the pixel classification of multichannel images with classify_image_class_gmmclassify_image_class_gmmClassifyImageClassGmmClassifyImageClassGmmClassifyImageClassGmmclassify_image_class_gmm is trained. add_samples_image_class_gmmadd_samples_image_class_gmmAddSamplesImageClassGmmAddSamplesImageClassGmmAddSamplesImageClassGmmadd_samples_image_class_gmm works analogously to add_sample_class_gmmadd_sample_class_gmmAddSampleClassGmmAddSampleClassGmmAddSampleClassGmmadd_sample_class_gmm. The ImageImageImageImageimageimage must have a number of channels equal to NumDimNumDimNumDimNumDimnumDimnum_dim, as specified with create_class_gmmcreate_class_gmmCreateClassGmmCreateClassGmmCreateClassGmmcreate_class_gmm. The training regions for the NumClassesNumClassesNumClassesNumClassesnumClassesnum_classes pixel classes are passed in ClassRegionsClassRegionsClassRegionsClassRegionsclassRegionsclass_regions. Hence, ClassRegionsClassRegionsClassRegionsClassRegionsclassRegionsclass_regions must be a tuple containing NumClassesNumClassesNumClassesNumClassesnumClassesnum_classes regions. The order of the regions in ClassRegionsClassRegionsClassRegionsClassRegionsclassRegionsclass_regions determines the class of the pixels. If there are no samples for a particular class in ImageImageImageImageimageimage an empty region must be passed at the position of the class in ClassRegionsClassRegionsClassRegionsClassRegionsclassRegionsclass_regions. With this mechanism it is possible to use multiple images to add training samples for all relevant classes to the GMM by calling add_samples_image_class_gmmadd_samples_image_class_gmmAddSamplesImageClassGmmAddSamplesImageClassGmmAddSamplesImageClassGmmadd_samples_image_class_gmm multiple times with the different images and suitably chosen regions. The regions in ClassRegionsClassRegionsClassRegionsClassRegionsclassRegionsclass_regions should contain representative training samples for the respective classes. Hence, they need not cover the entire image. The regions in ClassRegionsClassRegionsClassRegionsClassRegionsclassRegionsclass_regions should not overlap each other, because this would lead to the fact that in the training data the samples from the overlapping areas would be assigned to multiple classes, which may lead to a lower classification performance. Image data of integer type can be particularly badly suited for modeling with a GMM. RandomizeRandomizeRandomizeRandomizerandomizerandomize can be used to overcome this problem, as explained in add_sample_class_gmmadd_sample_class_gmmAddSampleClassGmmAddSampleClassGmmAddSampleClassGmmadd_sample_class_gmm.

Execution Information

Multithreading type: reentrant (runs in parallel with non-exclusive operators).
Multithreading scope: global (may be called from any thread).
Processed without parallelization.

This operator modifies the state of the following input parameter:

GMMHandleGMMHandleGMMHandleGMMHandleGMMHandlegmmhandle

During execution of this operator, access to the value of this parameter must be synchronized if it is used across multiple threads.

Parameters

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

Training image.

ClassRegionsClassRegionsClassRegionsClassRegionsclassRegionsclass_regions (input_object) region-array → object

Regions of the classes to be trained.

GMMHandleGMMHandleGMMHandleGMMHandleGMMHandlegmmhandle (input_control, state is modified) class_gmm → (handle)

GMM handle.

RandomizeRandomizeRandomizeRandomizerandomizerandomize (input_control) real → (real)

Standard deviation of the Gaussian noise added to the training data.

Default: 0.0

Suggested values: 0.0, 1.5, 2.0

Restriction: Randomize >= 0.0

Result

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