classify_image_class_lut — Classify a byte image using a look-up table.
classify_image_class_lut(Image : ClassRegions : ClassLUTHandle : )
classify_image_class_lut performs a pixel classification on a
multi-channel byte Image using a look-up table (LUT)
ClassLUTHandle. The operator can replace
classify_image_class_gmm, classify_image_class_knn,
classify_image_class_mlp and classify_image_class_svm.
The classification gets a major speed-up,
because the estimation of the class in every image point is no longer
necessary since every possible response of the GMM, KNN, MLP or SVM,
respectively, is stored in the LUT. This LUT classifier must be created
with the trained classifier in create_class_lut_gmm,
create_class_lut_knn, create_class_lut_mlp or
create_class_lut_svm, respectively, before
classify_image_class_lut can be used. For the classification the
parameters in create_class_gmm, create_class_knn,
create_class_mlp and create_class_svm, respectively,
are important: The byte Image must have the same number of channels
as specified by NumInput, NumFeatures or NumDim,
respectively. As result of the pixel classification
classify_image_class_lut passes NumOutput or
NumClasses regions in ClassRegions, respectively
Image (input_object) (multichannel-)image → object (byte)
Input image.
ClassRegions (output_object) region-array → object
Segmented classes.
ClassLUTHandle (input_control) class_lut → (handle)
Handle of the LUT classifier.
read_image (Image, 'patras')
gen_rectangle1 (Sea, 10, 10, 120, 270)
gen_rectangle2 (Deck, [170,400], [350,375], [-0.56192,-0.75139], \
[64,104], [26,11])
union1 (Deck, Deck)
gen_rectangle1 (Walls, 355, 623, 420, 702)
gen_rectangle2 (Chimney, 286, 623, -0.56192, 64, 33)
concat_obj (Sea, Deck, Classes)
concat_obj (Classes, Walls, Classes)
concat_obj (Classes, Chimney, Classes)
*
* create MLP classifier and train it with sample classes
create_class_mlp (3, 3, 4, 'softmax', 'principal_components', 3, \
42, MLPHandle)
add_samples_image_class_mlp (Image, Classes, MLPHandle)
train_class_mlp (MLPHandle, 200, 1, 0.01, Error, ErrorLog)
*
* create the LUT classifier
create_class_lut_mlp (MLPHandle, [], [], ClassLUTHandle)
*
* classify the image with the LUT
classify_image_class_lut (Image, ClassRegions, ClassLUTHandle)
If the parameters are valid, the operator
classify_image_class_lut returns the value 2 (H_MSG_TRUE). If
necessary an exception is raised.
create_class_lut_gmm,
create_class_lut_knn,
create_class_lut_mlp,
create_class_lut_svm
classify_image_class_gmm,
classify_image_class_knn,
classify_image_class_mlp,
classify_image_class_svm
create_class_lut_gmm,
create_class_lut_knn,
create_class_lut_mlp,
create_class_lut_svm,
create_class_lut_gmm
Foundation