CVS trevistaCAM - the smart camera addition to our innovative surface imaging range
The CVS trevistaCAM uses the patented shape from shading illumination system in combination with a powerful smart camera, pre-loaded with the inspection software. The CVS trevistaCAM is ideal for applications that require inspection of topographical and textural details of parts, even if they're challenging glossy / curved surfaces or trim parts.
- Self contained system with dome-shaped illumination and a 4Mpixel industrial-grade smart camera for the inspection of challenging surfaces.
- Micron level, automated inspection and presentation of defects.
- Ready to go, Shape from shading inspection detects elevations and depressions in the surface of the part.
3 reasons to use the CVS trevistaCAM
You want an out of the box solution – ready to go with minimal engineering
You need a cost effective system to read embossed codes on difficult surfaces
You want a reliable system
trevista is based on the patented shape-from-shading technology: diffuse structured lighting guarantees optimum illumination from different directions. Thus, even the most difficult shapes can be fully inspected. The trevista process closes the gap between 2D image processing and optical 3D shape recognition. It combines the speed of 2D image processing and the precision of 3D recognition.
- Topographic images are used for the three-dimensional presentation of surface shapes and the presentation of defect characteristics with depths of only a few microns
- Generation of a textured image for detection of brightness differences on the inspected components
- The trevista algorithm locates and classifies defects quickly, reliably and free of interference
CVS trevistaCAM variants
CVS trevistaCAM-INSPECT EXPRESS
Examples with CVS trevistaCAM
Example A: Euro coin
The coin example demonstrates how CVS trevistaCAM works: The slope images in x and y direction detect shape deviations in a specific orientation. The curvature image is invariant in orientation, and provides additional topographic information that can be used to distinguish between elevations and depressions. The texture image evaluates the brightness characteristics of the surface, allowing defects such as discoloration and rust to be clearly identified. These partial images are combined to give the final result image.
Example B: Membrane
Compact entry level system:
- Lighting, control unit, trevista algorithm, camera, lens and software
- Dimensions: 160 x 160 x 220 mm
- Resolution : 2048 x 2048 Pixel
- Plug & Play
- Field of view typically: 35 mm diameter
- Working distance typically: 20 mm
Intelligent camera: ADLINK NEON
- CMOSIS CMV4000
- Intel Atom Quad Core, 4 GB RAM, 32 GB SSD
- Windows 7 embedded
- Digital I/O, Ethernet, USB, VGA
Standard lens RICOH f = 35 mm
- Structured diffuse Dome light
- Temperature control
- Control unit
- Timing image acquisition sequence
- Modes: hardware-trigger / software-trigger
- 4 digital inputs, 3 digital outputs