apply_texture_inspection_model🔗
Short description🔗
apply_texture_inspection_model — Inspection of the texture within an image.
Signature🔗
apply_texture_inspection_model( image Image, out region NoveltyRegion, texture_inspection_model TextureInspectionModel, out texture_inspection_result TextureInspectionResultID )
Description🔗
The operator apply_texture_inspection_model compares
Image with the trained texture inspection model
TextureInspectionModel. Image can either be a single
image or a tuple of images. It is possible to pass either gray-scale
or multichannel images. Hereby, the operator expects that the passed
Image has the same number of channels than the model was trained
with. The runtime of the apply_texture_inspection_model scales
roughly linearly with the number of image channels. However, models
using colored images are generally better at detecting colored
texture defects.
Pixels that do not fit to the texture inspection model are returned
in NoveltyRegion. Furthermore, if 'gen_result_handle' has
been set to 'true' with set_texture_inspection_model_param,
the operator also returns the result handle
TextureInspectionResultID with more detailed information on
the texture classification. If 'gen_result_handle' is
set to 'false', TextureInspectionResultID is empty.
For an explanation of the concept of the texture inspection see the introduction of chapter Inspection / Texture.
For each pyramid level texture features are extracted and classified
with the corresponding GMM classifier. The resulting novelty score is
then compared to
the novelty threshold of the current pyramid level and classified as
defective or not. The defective pixels are collected in a novelty region for
each pyramid level. These novelty regions are then combined to the
final novelty region returned in NoveltyRegion. The novelty
regions of adjacent levels in the image pyramid are intersected with each
other. This step helps to improve the robustness towards noise within the
single pyramid level responses. The intersected novelty regions are then
added to the returned 'novelty_region'. If a pyramid level has no
adjacent pyramid level the region itself is added to the
'novelty_region'. If, for example, 'num_levels' is set to 1,
no adjacent pyramid level exists and the 'novelty_region' is the
novelty region of the first pyramid level.
If 'gen_result_handle' is set to 'true', the result handle
TextureInspectionResultID contains
novelty score images and the resulting novelty regions for each pyramid level.
This information is useful for debugging and fine tuning of the model
parameters (e.g., the novelty thresholds) and can be accessed with
get_texture_inspection_result_object.
Execution information🔗
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.
This operator returns a handle. Note that the state of an instance of this handle type may be changed by specific operators even though the handle is used as an input parameter by those operators.
This operator modifies the state of the following input parameter:
During execution of this operator, access to the value of this parameter must be synchronized if it is used across multiple threads.
Parameters🔗
Image (input_object) (multichannel-)image-array → object (byte / uint2 / real)
Image of the texture to be inspected.
NoveltyRegion (output_object) region-array → object
Novelty regions.
TextureInspectionModel (input_control) texture_inspection_model → (handle)
Handle of the texture inspection model.
TextureInspectionResultID (output_control, state is modified) texture_inspection_result → (handle)
Handle of the inspection results.
Example🔗
(HDevelop)
* Create texture inspection model
create_texture_inspection_model ('basic', TextureInspectionModel)
* Set parameters
set_texture_inspection_model_param (TextureInspectionModel, \
'gen_result_handle', 'true')
* Make this short example fast:
set_texture_inspection_model_param (TextureInspectionModel, \
'gmm_em_max_iter', 1)
* Read and add training images
read_image (TrainImage, 'carpet/carpet_01')
add_texture_inspection_model_image (TrainImage, TextureInspectionModel, \
Indices)
* Train the model
train_texture_inspection_model (TextureInspectionModel)
* Read and apply a test image
read_image (TestImage, 'carpet/carpet_02')
apply_texture_inspection_model (TestImage, DefectCandidates, \
TextureInspectionModel, \
TextureInspectionResultID)
Result🔗
The operator apply_texture_inspection_model returns the value 2 (H_MSG_TRUE)
if the given parameters are valid and within acceptable range.
Otherwise, an exception will be raised.
Combinations with other operators🔗
Combinations
Possible predecessors
train_texture_inspection_model
Possible successors
get_texture_inspection_result_object, get_texture_inspection_model_param, clear_texture_inspection_result, clear_texture_inspection_model
Module🔗
Matching