In machine vision applications, accuracy of the image far outweighs image appearance. This paper presents physically-accurate image synthesis as a flexible, practical tool for examining a large number of hardware/software configuration combinations for a wide range of parts. Synthetic images can efficiently be used to study the effects of vision system design parameters on image accuracy, providing insight into the accuracy and efficiency of image-processing algorithms in determining part location and orientation for specific applications, as well as reducing the number of hardware prototype configurations to be built and evaluated. We present results illustrating that physically accurate, rather than photo-realistic, synthesis methods are necessary to sufficiently simulate captured image gray-scale values. The usefulness of physically-accurate synthetic images in evaluating the effect of conditions in the manufacturing environment on captured images is also investigated. The prevalent factors investigated in this study are the effects of illumination, the sensor non-linearity and the finite-size pinhole on the captured image of retroreflective vision sensing and, therefore, on camera calibration was shown; if not fully understood, these effects can introduce apparent error in calibration results. While synthetic images cannot fully compensate for the real environment, they can be efficiently used to study the effects of ambient lighting and other important parameters, such as true part and environment reflectance, on image accuracy. We conclude with an evaluation of results and recommendations for improving the accuracy of the synthesis methodology.

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Enrollments in Mechanical Engineering programs continue to increase. Unfortunately, increases in faculty size have not kept pace at many universities, resulting in large course enrollments in even junior- and senior-level major courses. The primary goals of this study were to increase (or at least maintain) the quality of instruction, and increase student competency and understanding in a large lecture course having the same instructional personnel resources as a course with 60% of the enrollment. Hybrid and problem-based learning techniques, along with two optional weekly recitation sessions and an online discussion forum were incorporated into the course to meet these goals. The course, a classical controls course, is one in which course concepts are generally considered to be a bit abstract to a considerable percentage of the class. The instructor had previously taught the course several times, so a well-paced course schedule and solid foundation of course notes were already in place. Student evaluation instruments in previous offerings included weekly homework, bi-weekly short quizzes, two exams and the final exam. For the large lecture course (with an enrollment of 84 students), the evaluation instruments (homework, quizzes and exams) remained the same; however, the students formed self-selected triad teams. Approximately two-thirds of the quizzes, one-half of the homework and sixty percent of the final exam questions were assigned to the triad teams (the balance and both mid-term exams were individual submissions). The primary advantages of group quizzes and assignments were multi-fold: they facilitated group learning and peer-teaching to reinforce course concepts and allowed the instructor and teaching assistant to give the type of detailed feedback on submissions that would have been difficult or impossible to give on 84 individual submissions. Course notes (including short Echo360 modules), handouts and homework and quiz solutions were maintained on an online course management system (i.e., Blackboard); additionally, the use of an online threaded discussion forum, Piazza, allowed students to post/answer questions (anonymously, if desired) and follow discussions about course content. Team-based learning techniques were heavily used in latter course topics; the assigned readings, along with online course notes were used to prepare the students for the individual readiness assessment tests (RATs). Students discussed their answers on the RAT instruments in their triad groups (another opportunity for peer teaching) and disclosed group answers (which generally reflected a much higher level of understanding) to the entire class. Student assessment of course techniques and a comparison of traditional (lecture-based) and hybrid-/problem-based techniques will be used to assess the efficacy of the problem-based approach and to suggest improvements for future offerings.