classify_image_class_gmm — Classify an image with a Gaussian Mixture Model.
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.
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
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_gmm returns the value 2 (H_MSG_TRUE). If necessary an exception is raised.
classify_image_class_knn, classify_image_class_mlp, classify_image_class_svm, classify_image_class_lut, class_ndim_box, class_ndim_norm, class_2dim_sup