The isolated subset of data useful for the chosen inspection (image B) (here we have chosen to use the Gaussian curvature information).The reconstructed image based on the selected measurements (image A).The object captured by the camera under four lighting conditions (images 1 to 4).The above Figure 2 illustrates the entire process: These are used for the reconstruction/rendering of the 3D information in the 2D domain, making it ready for further processing by other libraries.įigure 2: Images of blister under various lighting conditions and inspection. Processįrom then on, the image capture of inspected objects is performed in multiple steps corresponding to the various lighting angles.Īt the user’s request, Photometric Stereo individually extracts a number of variables (normal to the surface, albedo, X & Y gradients, mean and Gaussian curvatures). How does it work?įor a given vision set up (positions and angles of the object to be inspected, the lights (typically 3 or 4) and the camera), the software tool first requires the calibration on a reference object, or the manual introduction of the set up’s precise geometric characteristics. It can be used as a preprocessing phase before other operations, such as code reading (with the EasyMatrixCode, EasyQRCode or EasyBarcode libraries), optical character recognition (EasyOCR), alignment (EasyMatch or EasyFind), measurement (EasyGauge) or defect detection (EasyObject or EasySegment). The Photometric Stereo algorithm is available in Euresys’ Open eVision Eas圓D library. Photometric Stereo is suitable for the detection or inspection of details (be they defects or information) present on the surface of objects. The different images are acquired in sequence, in synchronisation with the lighting, thus requiring only one camera. Euresys’ Photometric Stereo function estimates the orientation and albedo of each point of a surface by acquiring several images of the same surface taken from a single viewpoint, but under illumination from different directions.
One, probably lesser known, of these techniques is Photometric Stereo. Let’s mention structured light (including laser-scanning based triangulation), stereo or stereoscopic vision and time of flight sensors. Numerous techniques are used for extracting 3D information from scenes. Though a large majority of machine vision applications are solved using two-dimensional imaging, machine vision applications using or requiring 3D measurement and inspection are growing significantly.
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