add_samples_image_class_knnadd_samples_image_class_knnAddSamplesImageClassKnnadd_samples_image_class_knnAddSamplesImageClassKnnAddSamplesImageClassKnn (Operator)

Name

add_samples_image_class_knnadd_samples_image_class_knnAddSamplesImageClassKnnadd_samples_image_class_knnAddSamplesImageClassKnnAddSamplesImageClassKnn — Add training samples from an image to the training data of a k-Nearest-Neighbor classifier.

Signature

Description

add_samples_image_class_knnadd_samples_image_class_knnAddSamplesImageClassKnnadd_samples_image_class_knnAddSamplesImageClassKnnAddSamplesImageClassKnn adds training samples from the ImageImageImageImageImageimage to the k-Nearest-Neighbor (k-NN) given by KNNHandleKNNHandleKNNHandleKNNHandleKNNHandleKNNHandle. add_samples_image_class_knnadd_samples_image_class_knnAddSamplesImageClassKnnadd_samples_image_class_knnAddSamplesImageClassKnnAddSamplesImageClassKnn is used to store the training samples before a classifier is used for the pixel classification of multichannel images with classify_image_class_knnclassify_image_class_knnClassifyImageClassKnnclassify_image_class_knnClassifyImageClassKnnClassifyImageClassKnn. add_samples_image_class_knnadd_samples_image_class_knnAddSamplesImageClassKnnadd_samples_image_class_knnAddSamplesImageClassKnnAddSamplesImageClassKnn works analogously to add_sample_class_knnadd_sample_class_knnAddSampleClassKnnadd_sample_class_knnAddSampleClassKnnAddSampleClassKnn. The ImageImageImageImageImageimage must have a number of channels equal to NumDimNumDimNumDimNumDimNumDimnumDim, as specified with create_class_knncreate_class_knnCreateClassKnncreate_class_knnCreateClassKnnCreateClassKnn. ClassRegionsClassRegionsClassRegionsClassRegionsClassRegionsclassRegions must be a tuple containing of at least 2 regions. The order of the regions in ClassRegionsClassRegionsClassRegionsClassRegionsClassRegionsclassRegions 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 ClassRegionsClassRegionsClassRegionsClassRegionsClassRegionsclassRegions. With this mechanism it is possible to use multiple images to add training samples for all relevant classes to the k-NN classifier by calling add_samples_image_class_knnadd_samples_image_class_knnAddSamplesImageClassKnnadd_samples_image_class_knnAddSamplesImageClassKnnAddSamplesImageClassKnn multiple times with different images and suitably chosen regions. The regions in ClassRegionsClassRegionsClassRegionsClassRegionsClassRegionsclassRegions should contain representative training samples for the respective classes. Hence, they do not need to cover the entire image. The regions in ClassRegionsClassRegionsClassRegionsClassRegionsClassRegionsclassRegions should not overlap each other, as these samples from overlapping areas would be assigned to multiple classes in the training data, which may lead to a lower classification performance.

Parallelization

• 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:

• KNNHandleKNNHandleKNNHandleKNNHandleKNNHandleKNNHandle

Parameters

Result

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

Possible Predecessors

create_class_knncreate_class_knnCreateClassKnncreate_class_knnCreateClassKnnCreateClassKnn

Possible Successors

train_class_knntrain_class_knnTrainClassKnntrain_class_knnTrainClassKnnTrainClassKnn

Alternatives

add_sample_class_knnadd_sample_class_knnAddSampleClassKnnadd_sample_class_knnAddSampleClassKnnAddSampleClassKnn

See also

classify_image_class_knnclassify_image_class_knnClassifyImageClassKnnclassify_image_class_knnClassifyImageClassKnnClassifyImageClassKnn, add_sample_class_knnadd_sample_class_knnAddSampleClassKnnadd_sample_class_knnAddSampleClassKnnAddSampleClassKnn, add_samples_image_class_svmadd_samples_image_class_svmAddSamplesImageClassSvmadd_samples_image_class_svmAddSamplesImageClassSvmAddSamplesImageClassSvm

Module

Foundation