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A new reverse compensation CAD model is produced and loaded into a RP machine for practical prototype processing, to increase the accuracy of the process.
Second, dynamic reverse compensation employed to obtain a new CAD model, which is then loaded into a RP machine for practical prototype processing, to increase the accuracy of the process.
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In this way, some works have shown that the major challenges of rapid prototyping image processing applications in multiprocessor system-on-chip design are mainly the programming model, the design flow, and the communication infrastructure.
By exploiting strategies in real-time serial communication and image processing, the prototype acquires uniformly dense point cloud from a geometric specimen.
Indeed, our general problem requires the rapid hardware prototyping of complex image processing applications (multitasks applications) in embedded devices and multiprocessors design in this case.
More precisely, our goal is to develop rapid prototyping tools for image processing applications, using parallel homogeneous architecture, as will be described in the next section.
Based on these improvements, a 2x2 mm area could be imaged in less than 600 ms. The image processing for the prototype system was done in Matlab which is very versatile and easy to use, but not particularly efficient.
This work presents the use of this rapid prototyping methodology suitable for image processing systems and heterogeneous multicomponent architectures.
We describe the different methods of integrating CT or MRI with image processing and rapid prototyping technologies in producing stereolithographic models.
(a) The prototype camera unit and (b) image processing unit.
Both flows play key roles in digital image processing as well as provide prototypes for modeling motion of interfaces in a variety of physical settings.
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