An edge detection framework conjoining with IMU data for assisting indoor navigation of visually impaired persons

Smartphone applications based on object detection techniques have recently been proposed to assist visually impaired persons with navigating indoor environments. In the smartphone, digital cameras are installed to detect objects which are important for navigation. Prior to detect the interested objects from images, edges on the objects have to be identified. Object edges are difficult to be detected accurately as the image is contaminated by strong image blur which is caused by camera movement. Although deblurring algorithms can be used to filter blur noise, they are computationally expensive and not suitable for real-time implementation. Also edge detection algorithms are mostly developed for stationary images without serious blur. In this paper, a modified sigmoid function (MSF) framework based on inertial measurement unit (IMU) is proposed to mitigate these problems. The IMU estimates blur levels to adapt the MSF which is computationally simple. When the camera is moving, the topological structure of the MSF is estimated continuously in order to improve effectiveness of edge detections. The performance of the MSF framework is evaluated by detecting object edges on video sequences associated with IMU data. The MSF framework is benchmarked against existing edge detection techniques and results show that it can obtain comparably lower errors. It is further shown that the computation time is significantly decreased compared to using techniques that deploy deblurring algorithms, thus making our proposed technique a strong candidate for reliable real-time navigation

Non-Destructive Testing Inspection for Metal Components Produced Using Wire and Arc Additive Manufacturing

Funding Information: JPO acknowledges funding by national funds from FCT—Fundação para a Ciência e a Tecnologia, I.P., in the scope of the projects LA/P/0037/2020. This activity has received funding from the European Institute of Innovation and Technology (EIT)—Project Smart WAAM: Microstructural Engineering and Integrated Non-Destructive Testing. This body of the European Union receives support from the European Union’s Horizon 2020 research and innovation programme. Publisher Copyright: © 2023 by the authors.The wire and arc additive manufacturing (WAAM) process enables the creation and repair of complex structures based on the successive deposition of fed metal in the form of a wire that is fused with an electric arc and then solidifies. The high number of depositions required to create or repair parts increases the likelihood of defect formation. If these are reliably detected during manufacturing, timely correction is possible. However, high temperatures and surface irregularity make inspection difficult. Furthermore, depending on the size, morphology, and location of the defect, the part can be rejected. Recent studies have shown that non-destructive testing (NDT) based on different physical phenomena for the timely, reliable, and customized detection of defects can significantly reduce the rejection rate and allow in-line repair, which consequently reduces waste and rework. This paper presents the latest developments in NDT for WAAM and its limitations and potential.publishersversionpublishe