classify_image_class_knnT_classify_image_class_knnClassifyImageClassKnnClassifyImageClassKnnclassify_image_class_knn (Operator)
Name
classify_image_class_knnT_classify_image_class_knnClassifyImageClassKnnClassifyImageClassKnnclassify_image_class_knn — Classify an image with a k-Nearest-Neighbor classifier.
Signature
Description
classify_image_class_knnclassify_image_class_knnClassifyImageClassKnnClassifyImageClassKnnClassifyImageClassKnnclassify_image_class_knn performs a pixel classification
with a k-Nearest-Neighbor classifier (k-NN) KNNHandleKNNHandleKNNHandleKNNHandleKNNHandleknnhandle on the
multichannel image ImageImageImageImageimageimage. Before calling
classify_image_class_knnclassify_image_class_knnClassifyImageClassKnnClassifyImageClassKnnClassifyImageClassKnnclassify_image_class_knn the k-NN classifier must be trained with
train_class_knntrain_class_knnTrainClassKnnTrainClassKnnTrainClassKnntrain_class_knn. ImageImageImageImageimageimage must have NumDimNumDimNumDimNumDimnumDimnum_dim
channels, as specified with create_class_knncreate_class_knnCreateClassKnnCreateClassKnnCreateClassKnncreate_class_knn. 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_knnadd_samples_image_class_knnAddSamplesImageClassKnnAddSamplesImageClassKnnAddSamplesImageClassKnnadd_samples_image_class_knn. The parameter
RejectionThresholdRejectionThresholdRejectionThresholdRejectionThresholdrejectionThresholdrejection_threshold can be used to reject pixels that have
an uncertain classification. RejectionThresholdRejectionThresholdRejectionThresholdRejectionThresholdrejectionThresholdrejection_threshold represents
a threshold on the distance to the nearest neighbor returned by the
classification. All pixels having a probability below
RejectionThresholdRejectionThresholdRejectionThresholdRejectionThresholdrejectionThresholdrejection_threshold are not assigned to any class.
DistanceImageDistanceImageDistanceImageDistanceImagedistanceImagedistance_image contains the distance of each pixel to its nearest
neighbor.
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 * (real)
Segmented classes.
DistanceImageDistanceImageDistanceImageDistanceImagedistanceImagedistance_image (output_object) image → objectHImageHObjectHImageHobject *
Distance of the pixel's nearest neighbor.
KNNHandleKNNHandleKNNHandleKNNHandleKNNHandleknnhandle (input_control) class_knn → HClassKnn, HTupleHHandleHTupleHtuple (handle) (IntPtr) (HHandle) (handle)
Handle of the k-NN classifier.
RejectionThresholdRejectionThresholdRejectionThresholdRejectionThresholdrejectionThresholdrejection_threshold (input_control) real → HTuplefloatHTupleHtuple (real) (double) (double) (double)
Threshold for the rejection of the classification.
Default:
0.5
Suggested values:
0.0, 0.1, 0.2, 0.3, 5.0, 10.0, 255.0
Restriction:
RejectionThreshold >= 0.0
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_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)
Result
If the parameters are valid, the operator
classify_image_class_knnclassify_image_class_knnClassifyImageClassKnnClassifyImageClassKnnClassifyImageClassKnnclassify_image_class_knn returns the value 2 (
H_MSG_TRUE)
. If
necessary an exception is raised.
Possible Predecessors
train_class_knntrain_class_knnTrainClassKnnTrainClassKnnTrainClassKnntrain_class_knn,
read_class_knnread_class_knnReadClassKnnReadClassKnnReadClassKnnread_class_knn
Alternatives
classify_image_class_svmclassify_image_class_svmClassifyImageClassSvmClassifyImageClassSvmClassifyImageClassSvmclassify_image_class_svm,
classify_image_class_mlpclassify_image_class_mlpClassifyImageClassMlpClassifyImageClassMlpClassifyImageClassMlpclassify_image_class_mlp,
classify_image_class_gmmclassify_image_class_gmmClassifyImageClassGmmClassifyImageClassGmmClassifyImageClassGmmclassify_image_class_gmm,
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_knnadd_samples_image_class_knnAddSamplesImageClassKnnAddSamplesImageClassKnnAddSamplesImageClassKnnadd_samples_image_class_knn,
create_class_knncreate_class_knnCreateClassKnnCreateClassKnnCreateClassKnncreate_class_knn
Module
Foundation