Detecting image edges in IOT nodes without FPU

Abstract

AbstractInternet of Things (IoT) applications continue to expand into new applications with a growing need for image processing on the edge. Many edge devices are resource limited microcontrollers, which significantly prohibits many of the mature image processing algorithms. This paper proposes an approach optimized, for resource constrained processors removing the need for computationally expensive floating point arithmetic by using a framework based on unsigned integer arithmetic for image processing. The proposed framework (OptInt) is demonstrated using edge detection algorithms evaluated on two typical low-power IoT-ready micro-controllers and for comparison a more powerful Raspberry Pi. Results indicate that the OptInt approach for basic image processing in resource constrained devices reduces the computation time as well as the memory requirements, thereby allowing for more edge computing capabilities in these devices. Furthermore, the images produced using OptInt produce results of similar quality to mature edge detection algorithms.