Image processing applications expose an intrinsic resilience to faults. In this application field the classical Duplication with Comparison (DWC) scheme, where output images are discarded as soon as the two replicas' outputs differ for at least one pixel, may be over-conseravative. This paper introduces a novel lightweight fault detection scheme for image processing applications; i) it extends the DWC scheme by substituting one of the two exact replicas with a faster approximated one; and ii) it features a Neural Network-based checker designed to distinguish between usable and unusable images instead of faulty/unfaulty ones. The application of the hardening scheme on a case study has shown an execution time reduction from 27% to 34% w.r.t. the DWC, while guaranteeing a comparable fault detection capability.

An Approximation-based Fault Detection Scheme for Image Processing Applications

Biasielli M.;Cassano L.;Miele A.
2020

Abstract

Image processing applications expose an intrinsic resilience to faults. In this application field the classical Duplication with Comparison (DWC) scheme, where output images are discarded as soon as the two replicas' outputs differ for at least one pixel, may be over-conseravative. This paper introduces a novel lightweight fault detection scheme for image processing applications; i) it extends the DWC scheme by substituting one of the two exact replicas with a faster approximated one; and ii) it features a Neural Network-based checker designed to distinguish between usable and unusable images instead of faulty/unfaulty ones. The application of the hardening scheme on a case study has shown an execution time reduction from 27% to 34% w.r.t. the DWC, while guaranteeing a comparable fault detection capability.
Proceedings of the 2020 Design, Automation and Test in Europe Conference and Exhibition, DATE 2020
978-3-9819263-4-7
Approximate Computing
Convolutional Neural Networks
Fault Detection
Image Processing
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/1150422
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