classify_image_class_knn — Classify an image with a k-Nearest-Neighbor classifier.
classify_image_class_knn performs a pixel classification with a k-Nearest-Neighbor classifier (k-NN) KNNHandle on the multichannel image Image. Before calling classify_image_class_knn the k-NN classifier must be trained with train_class_knn. Image must have NumDim channels, as specified with create_class_knn. 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_knn. The parameter RejectionThreshold can be used to reject pixels that have an uncertain classification. RejectionThreshold represents a threshold on the distance to the nearest neighbor returned by the classification. All pixels having a probability below RejectionThreshold are not assigned to any class. DistanceImage contains the distance of each pixel to its nearest neighbor.
Distance of the pixel's nearest neighbor.
Handle of the k-NN classifier.
Threshold for the rejection of the classification.
Default value: 0.5
Suggested values: 0.0, 0.1, 0.2, 0.3, 5.0, 10.0, 255.0
Restriction: RejectionThreshold >= 0.0
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_knn (3, KNNHandle) add_samples_image_class_knn (Image, Classes, KNNHandle) get_sample_num_class_knn (KNNHandle, NumSamples) train_class_knn (KNNHandle, , ) classify_image_class_knn (Image, ClassRegions, DistanceImage, KNNHandle, 0.5) dev_display (ClassRegions) clear_class_knn (KNNHandle)
If the parameters are valid, the operator classify_image_class_knn returns the value 2 (H_MSG_TRUE). If necessary an exception is raised.
classify_image_class_svm, classify_image_class_mlp, classify_image_class_gmm, classify_image_class_lut, class_ndim_box, class_ndim_norm, class_2dim_sup