The course is aimed at studying the vision-based 3D measuring techniques by means of the analysis of the theory and immediate application of it in the development of 3D scanning prototypes in the laboratory. This hands-on approach allows the students to participate actively to the lessons. The first part of the course develops the basic concepts related to the image acquisition and processing techniques. These concepts are used in the second part of the course to develop prototypes of scanners working with different approaches. The course will include the description of many real applications of 3D vision systems developed by the professor and his staff in cooperation with other Universities and Companies.

Once the student has passed the exam, the student will gain the following knowledge and understanding:

1. know the fundamentals of image acquisition and know how to set-up an image acquisition device,
2. be able to understand the critical issues in a specific 3D measurement application in order to find the correct solution,
3. be able to understand and describe the working principle of the most common 3D scanners, and be able to estimate the uncertainty associated to the measurement.

Furthermore, the student will gain the following application abilities:

1. design the appropriate measurement approach for 3D vision-based measurements in the most common industrial applications,
2. correctly select the most appropriate hardware for each specific 3D scanning application,
3. propose a test methodology for the performance qualification of 3D vision-based measuring systems.

Image acquisition techniques and systems: introduction to the image acquisition techniques, line scan and area scan sensors, CCD and CMOS technologies, frame grabbers, buses to connect digital cameras to the image processing units (USB, IEEE 1394, GigaEthernet, CameraLink). Smart cameras.

Image preprocessing: operators on single pixels, on image subsets and on the full image. Convolution operators and image transformation. 2D camera calibration to compensate for perspective and distortion due to the lens.

Image processing algorithms for measurements: description and use of the state of the art image processing techniques to extract measurements from images: edge detection, blob analysis, pattern matching and geometric matching.

3D measurements and scanning of shapes. Theory of image generation: pinhole cameras, optical aberration modelling. Techniques for the calibration of stereoscopic system and algorithms for 3D measurements. Stereoscopy theory and applications. Pose estimation for 3D tracking of targets with a single camera. Structured light scanners and Fourier Trasnform Profilometry.

3D Digital image correlation: the digital image correlation for 3D shape recovery and for the estimation of 3D strain field. Techniques to enhance the accuracy of the measurement result in DIC. Effect of motion on scanning accuracy.

3D data processing and storage: algorithms for point clouds processing, standard file formats for 3D data management and storing (VRML, IGES, STL,…).

Note that the slides used during the lesson will be available for the students in advances. The slides contain all the information needed for the course. The support books listed in the references can be useful for further analysis of the topics but are not compulsory.

There are no strict requirements, as pre-requisites. A basic background of the main engineering topics is  enough.

The students, alone or in small group of 2 or 3 people, will be asked to develop a project in the ambit of the course. The professor will assign the topic of the project also considering the main interest of the student. The professor, to offer the students the necessary support, will periodically review the development of the projects.

Students’ skills and knowledge will be evaluated by an oral exam that will mainly focus on the discussion of the developed project. Every group of students is asked to prepare a final report on the project and bring it to the final exam, where the defense of the work will be done.

In the oral exam each student is expected to demonstrate that the project has been developed setting-up the image acquisition system correctly (correct measurement approach and hardware selection), taking into account the potential critical issues for the specific application and evaluating correctly the quality of the obtained results.

Furthermore, the students need to show good capability to present their job and to discuss it with proper technical language, justify the choices and assumptions, after having shown good critical approaches to the problems faced in the work.

In particular chapter 5 is useful for the course.