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The effects which are produced by pearlescent pigments are intimately connected to optics and the interaction of light with matter. Pearlescent pigments are optical filters which reflect and transmit light which falls upon them. In order to understand pearlescent pigments, therefore it is first necessary to understand some of the basic laws of optics. I would like to review some of these laws to talk about light and its interaction with matter, how it can be separated into its components, the laws of reflection and refraction and how all of these laws apply to pearlescent pigments.

The introduction of video display terminals may exacerbate lighting problems already present in the workplace. The sources and characteristics of glare are described. Glare control measures, including the location and design of lighting systems, managing outdoor light and using screen filters and hoods, are reviewed.

The purpose of this paper is to analyze and show how to avoid the interference in infrared (IR) temperature field measurement during welding.

First, the hardware used in this experiment is described. In this paper, these interferences are first classified into diffuse and specular reflection based on reflection model, and are restrained, respectively. Finally, IR temperature is calibrated by thermocouple.

The specular reflection is the primary interference which causes high light zone. And it can be transferred out of welding seam when the IR thermography is placed perpendicularly to welding seam.

The paper provides a new IR measure method and detailed analysis about the interferences in applying IR temperature sensing.

The technique described in this paper consists of the examination of surface strains in a metal component with optically sensitive material bonded to the component and the analysis of the photoelastic pattern produced under load by means of polarized light reflected from the surface of the metal. The original investigations cover in considerable detail the development of the technique and the results obtained, using the photoelastic materials Catalin 800, C.R.39, and the Marco Resin, S.B.26C, and S.B.28C, in conjunction with light alloy, magnesium and mild steel. The fundamental problem of producing good adhesion between the photoelastic material and the metal surface coupled with satisfactory light reflexion from the latter comprised the major part of the initial investigations. Results of the measurement of both elastic and plastic stress concentrations at holes in plates subjected to uniform tension are presented, together with a qualitative analysis of the effect on stress distribution of the variation of the pin to hole clearance in lugs. Owing to the fairly extensive nature of the original investigations it has only been possible to outline the more salient features of the work undertaken. The term ‘Metaplastic’ is suggested to describe concisely the use of compound specimens for the photoelastic applications considered.

Studies the measurement and objective evaluation method of fabric lustre. Selects seven parameters at a two‐dimensional distribution curve of reflected light under natural light and polarized light and refines from them four independent variations by the method of main composition analysis. Using regression analysis with the results of subjective evaluation, finds that fabric lustre has distinct regional distribution on the figures of M1 and M2, so it can be used as a general test method.

Describes the rapid technical development that took place in the lighting industry in the 1980s, driven by energy cost pressures. Discusses product development, office lighting problems, legislation, changing working needs, new design approaches, HF fluorescent lighting, maintenance, and energy and lighting. Concludes that both economic pressures and users′ demand for better quality lighting are dictating a more professional approach to lighting scheme design.

When using a machine vision inspection system for rail surface defect detection, many complex factors such as illumination changes, reflection inequality, shadows, stains and rust might inevitably deform the scanned rail surface image. This paper aims to reduce the influence of these factors, a pipeline of image processing algorithms for robust defect detection is developed.

First, a new inverse Perona-Malik (P-M) diffusion model is presented for image enhancement, which takes the reciprocal of gradient as feature to adjust the diffusion coefficients, and a distinct nearest-neighbor difference scheme is introduced to select proper defect boundaries during discretized implementation. As a result, the defect regions are sufficiently smoothened, whereas the faultless background remains unchanged. Then, by subtracting the diffused image from the original image, the defect features will be highlighted in the difference image. Subsequently, an adaptive threshold binarization, followed by an attribute opening like filter, can easily eliminate the noisy interferences and find out the desired defects.

Using data from our developed inspection apparatus, the experiments show that the proposed method can attain a detection and measurement precisions as high as 93.6 and 85.9 per cent, respectively, while the recovery accuracy remains 93 per cent. Additionally, the proposed method is computationally efficient and can perform robustly even under complex environments.

A pipeline of algorithms for rail surface detection is proposed. Particularly, an inverse P-M diffusion model with a distinct discretization scheme is introduced to enhance the defect boundaries and suppress noises. The performance of the proposed method has been verified with real images from our own developed system.

This paper aims to solve the issue of target positioning in auto stiffener bonder (ASB) systems for flexible printed circuits.

The proposed approach uses Phong’s bidirectional reflectance distribution function (BRDF) model to simulate the reflection of light off a target in ASB systems to predict the current pose of the target based on image brightness, update the template, decrease the initial errors in the template and narrow down the search range.

The experimental results indicate that the proposed approach can predict the inclination angle of the target with precision, presenting angle prediction errors of less than three degrees. Furthermore, with larger inclined angles, the overall matching errors were less than 1.5 pixels. Comparisons with the unmodified matching algorithm revealed that the proposed approach resulted in 65 per cent less calculation time for the algorithm and 14 per cent higher overall work efficiency in the ASB system.

The edge-based perspective shape matching algorithm was modified using the Phong BRDF model and enhanced algorithm efficiency with the target pose prediction method while ensuring the precision and robustness of the system. The proposed approach has high potential value and can be expanded to recognition systems for objects with varying inclination angles and highly reflective surfaces.

Effective rail surface defects detection method is the basic guarantee to manufacture high-quality rail. However, the existed visual inspection methods have disadvantages such as poor ability to locate the rail surface region and high sensitivity to uneven reflection. This study aims to propose a bionic rail surface defect detection method to obtain the high detection accuracy of rail surface defects under uneven reflection environments.

Through this bionic rail surface defect detection algorithm, the positioning and correction of the rail surface region can be computed from maximum run-length smearing (MRLS) and background difference. A saliency image can be generated to simulate the human visual system through some features including local grayscale, local contrast and edge corner effect. Finally, the meanshift algorithm and adaptive threshold are developed to cluster and segment the saliency image.

On the constructed rail defect data set, the bionic rail surface defect detection algorithm shows good recognition ability on the surface defects of the rail. Pixel- and defect-level index in the experimental results demonstrate that the detection algorithm is better than three advanced rail defect detection algorithms and five saliency models.

The bionic rail surface defect detection algorithm in the production process is proposed. Particularly, a method based on MRLS is introduced to extract the rail surface region and a multifeature saliency fusion model is presented to identify rail surface defects.

The rapid advances in recent years made within the field of fibre optics and opto‐electronics open up new opportunities within many areas.