An Analytic Model for Embedded Machine Vision: Architecture and Performance Exploration

This paper represents a model to analyze the performance of an embedded machine vision system. Such an application is computationally expensive and often is a challenging problem in the eld of embedded systems. A model is derived to analyze the performance. It predicts system performance with minimal efforts and costs over a wide range of processor architectures. Specically, image segmentation is evaluated with the microprocessor technology. In the same way, a custom logic is designed with the help of the model