Industrial vision and automation

Abstract

This volume of Measurement Science and Technology contains a Special Feature on Industrial Vision and Automation. The special feature puts together research articles within the common denominator of Industrial Vision & Automation, especially for evaluation of various materials. This tried to demonstrate the breadth of applications for which one can use various vision systems, together with very recent research developments, some clear demonstrations of the method at work in applications and some of the necessary background theory that underpins the basic vision modalities. This special feature based on the adopted imaging methodology and the principles involved. Further articles in this Special Feature are sub-classified in to optical, thermal, X-ray and acoustical vision modalities as presented below with a brief description of the accepted manuscripts in each sub-section. Optical Vision Systems: An alternative technique is proposed to improve the visual detection rate of longitudinal conveyor belt tears by Gongxian Wang et al [1]; Automatic defect detection in multi-crystalline solar wafers using deep learning is presented by Du-Ming Tsai et al [2] Thermo-Vision Systems: An efficient denoising CAE with U-net architecture is proposed for thermal data to solve the problem of an insufficient dataset has been demonstrated in the work of Xiaoyuan Li et al [3]; Exploratory factor analysis for defect identification with active thermography is presented by Kai-Lun Huang et al [4]; X-ray Vision Systems: Coded aperture x-ray computed tomography `by sparsity-driven deterministic sampling strategy is demonstrated by Munnu Sonkar et al [5]; Acoustical Vision Systems: Phase velocity measurement of dispersive wave modes by Gaussian peak-tracing using f-k transform is presented by Bikash Ghose et al [6]; Coplanar electrical/ultrasonic dual-modality tomography for water continuous gas/oil/water three-phase distribution imaging is demonstrated by Guanghui Liang et al [7]; Defect visualization of cylindrical and conical CFRP lattice structures using rotational ultrasonic propagation imager is highlighted by J H An et al [8]; We are sure that readers will find this as a valuable special feature and a useful reference resource. Finally, we would like to thank all the authors for their contributions, the referees for their effort to thoroughly review the manuscripts by providing their valuable feedback to enhance the quality and the entire Editorial Board of Measurement Science and Technology for their constant support.