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Gexcel
JRC 3D Reconstructor
PRE-PROCESSING
JRC 3D Reconstructor Pre-processing
In this tutorial you will learn how to
Filter/Pre-process data
- automatic noise removal
- automatic computation
1. Overview 5. Contacts4. Results2. Noise Removal 3. Computation
GEXCEL
JRC 3D Reconstructor Pre-processing
Load a Grid point cloud
The toolbar reminds the user the suggested workflow steps
Pre-processing is the first workflow step after scan import. All the grid point clouds have to be pre-processed before going on with data elaboration even though the data have been already filtered in a third party software.
1. Overview 5. Contacts4. Results2. Noise Removal 3. Computation
GEXCEL
JRC 3D Reconstructor Pre-processing
IMPORTANT NOTE: preprocessing step works only with Grid Cloud of Points A Grid cloud of point can be viewed as “image” where the
number of pixels (pix) are equal to the number of point the scanner has acquired (valid and invalid).
In the preprocessing parameter you will find MASK BORDER (pix). This parameter
define the dimension in pixels of a square mask (“the kernel of the filter “), which give
you the possibility to set up how many points (=pixels) you want to take into account
around the point you are analysing.
For example:
Mask border [pix] = 1 means a square mask of 3 x 3 points around the central one to be filtered. The square mask (of side 2·border+1) is centred at the current pixel
Mask border [pix] = 2 -> 5 x 5 windows
According to the Mask border dimension the filter will have different effects following
detailed
2D pixels of
the Grid 3D points RGB value
1. Overview 5. Contacts4. Results2. Noise Removal 3. Computation
GEXCEL
JRC 3D Reconstructor Pre-processing
Select one or more Grid point clouds Press the button or Right mouse button Preprocessing
For each grid point cloud a set of filters and computation can be set-up and applied.
1. Overview 5. Contacts4. Results2. Noise Removal 3. Computation
GEXCEL
JRC 3D Reconstructor Pre-processing
Pre-processing is applied for 2 main purposes:
1) noise removal filter for raw data
2) addition of extra information to raw grid for further processing steps (i.e. registration, meshing, etc.)
3 noise removal filters can be applied to improve Grid quality (n. 1,2,4)
4 options are available for each raw
3 computations can be done to derive and add information to Grid Raw data (n. 3,5,6)
1. Overview 5. Contacts4. Results2. Noise Removal 3. Computation
GEXCEL
JRC 3D Reconstructor Pre-processing
Filter to remove points according to range distance or reflectance values: Min/Max range [m]: lower/upper threshold of the rangeAll pixels outside this range will be filteredMin/Max reflectance [reflectance value between 0 and 1]All measurements that have an intensity value outside the given interval will be filtered
Filter to smooth the point cloud from local noise roughness.For each point (=pixel) the software assigns the median value calculated using the N point in the square mash centered on the same point.For example Mask border=1 means a 3x3 windows, so the median is calculated according to 9 points. Larger is the Mask border, smoother is the final point cloud
Filter to remove wrong points aligned along the laser ray direction (for example points close to edges – see next slide -, or points viewed from a steep angle, or mixed points from phase shift laser). Defined the laser ray as the vector between the scanner and the acquired point (in red), the software calculates the angle between the laser ray and the vector connecting the center point with each points in the mask. If at list one angle is < the Min incident angle, the acquired point is deleted. Higher is the Mask border, more points will be deleted. Higher is the Min incident angle, more points will be deleted
Laser ray
1. Overview 5. Contacts4. Results2. Noise Removal 3. Computation
GEXCEL
JRC 3D Reconstructor Pre-processing
Example of mixed points to be filtered: points close to edges
1. Overview 5. Contacts4. Results2. Noise Removal 3. Computation
GEXCEL
JRC 3D Reconstructor Pre-processing
During the pre-processing it is possible to remove points according to a user defined mask
1. Select a scan and save a 2D image from your scan
2. Edit in black color the
area to delete using any
external software (i.e. Photo Point, Coral Draw, etc.)
3. Run pre-processing: set as Noise
Removal the Mask Filter and assign the
absolute path of your edited image
4. The black points of the
mask will be
automatically delete
1. Overview 5. Contacts4. Results2. Noise Removal 3. Computation
GEXCEL
JRC 3D Reconstructor Pre-processing
Computes the local surface tangent plane for each point, based on the neighbourhood of the pixel.Smaller is the mask border more local will be the tangent plane calculation.
Filter to computes geometrically significant line features from the grid point cloud. Two types of edges are extracted:- Depth discontinuities (or jump edges) that occur when the scanner hits an occlusion and therefore the measured range jumps from a foreground to a background value.- Orientation discontinuities (or crease edges) that occur when the object has a sudden change of its surface orientation.
Mask border [pix]: the kernel of the filter is a square mask (of side 2·border+1) centred at the current pixel.Min depth discontinuity to flag [m]: set absolute depth discontinuity according to the object scale.Min orientation discontinuity to flag [deg]: the current point is marked if its normal differs from the adjacent ones of at least this angle.
Edge detection results will be used fro Meshing (see Quick Guide n.5 Meshing&MeshEditing)
1. Overview 4. Results3. Computation 5. Contacts2. Noise Removal
GEXCEL
JRC 3D Reconstructor Pre-processing
Computes a confidence value for each measurement, which is
a measure for the reliability of the given range measurement.
The accuracy does not only depend on the type of scanner
used, but amongst others also on the following factors:
- incident angle between the laser beam and the tangent plane
of the target
- distance to the target
- material of the object
- intensity of the reflected signal
The confidence value is computed as a weighted sum of the surface normal, the range value and the reflectance value.
Min/Max range [m]: the range is weighted by normalizing it within this interval
Scale factor: the confidence value calculated for each pixel is multiplied with this scale. Thus the user has the possibility to
decrease or increase the weight for a given scan manually, for example because a scanner with higher accuracy has been used
during acquisition.
Weight of range/reflectance/inclination: modify the weight as desired
1. Overview 4. Results3. Computation 5. Contacts2. Noise Removal
GEXCEL
JRC 3D Reconstructor Pre-processing
The pre-processing can use the multi-processor characteristics of your PC
You can run the pre-processing
from the same scan several times.
If you need to reset the previous
preprocessing effects, switch on the
Use back up option
Run the pre-preprocessing and view the results!
1. Overview 4. Results3. Computation 5. Contacts2. Noise Removal
GEXCEL
JRC 3D Reconstructor Pre-processing
Is possible to save pre-processing parameters and load them for other scans or projects
The preprocessing
parameters are
saved in a XML file
1. Overview 4. Results3. Computation 5. Contacts2. Noise Removal
GEXCEL
JRC 3D Reconstructor Pre-processing
View the Pre-processing results: preprocessed scan has the P icon
Noise removal filters are visible
looking in detail the point clouds.
i.e. false mixed points are cleaned
Compute filters add new information layers to the Grid
Inclination Confidence
Edges extraction:
Right button of the mouse on the
Grid filter tool extract edges
Edges can be exported as 3D DXF polylines
1. Overview 4. Results3. Computation 5. Contacts2. Noise Removal
GEXCEL
JRC 3D Reconstructor Pre-processing
If you need some more information, please contact
our Gexcel Sales Team writing to
Phone (+39) 030 6595001
1. Overview 4. Results3. Computation 5. Contacts2. Noise Removal
GEXCEL