Quality grading of painted slates using texture analysis

This paper details the development of an automated vision-based solution for identification of paint and substrate defects on painted slates. The developed vision system consists of two major components. The first component of the system addresses issues including the mechanical implementation and interfacing the inspection system with the sensing and optical equipment. The second component involves the development of an image processing algorithm that is able to identify the visual defects present on the slate surface. The process of imaging the slate proved to be very challenging as the slate surface is darkly coloured and presents depth non-uniformities. Hence, a key issue for this inspection system was to devise an adequate illumination system that was able to accommodate challenges including the slates’ surface depth non-uniformities and vibrations generated by the conveying system. The visual defects are detected using a novel texture analysis solution where the greyscale (tonal characteristics) and texture information are embedded in a composite model. The developed inspection system was tested for robustness and experimental results are presented

Automatic inspection of surface defects in die castings after machining

A new camera based machine vision system for the automatic inspection of surface defects in aluminum die casting was developed by the authors. The problem of surface defects in aluminum die casting is widespread throughout the foundry industry and their detection is of paramount importance in maintaining product quality. The casting surfaces are the most highly loaded regions of materials and components. Mechanical and thermal loads as well as corrosion or irradiation attacks are directed primarily at the surface of the castings. Depending on part design and processing techniques, castings may develop surface discontinuities such as cracks or tears, inclusions due to chemical reactions or foreign material in the molten metal, and pores that greatly influence the material ability to withstand these loads. Surface defects may act as a stress concentrator initiating a fracture point. If a pressure is applied in this area, the casting can fracture. The human visual system is well adapted to perform in areas of variety and change; the visual inspection processes, on the other hand, require observing the same type of image repeatedly to detect anomalies. Slow, expensive, erratic inspection usually is the result. Computer based visual inspection provides a viable alternative to human inspectors. Developed by authors machine vision system uses an image processing algorithm based on modified Laplacian of Gaussian edge detection method to detect defects with different sizes and shapes. The defect inspection algorithm consists of three parameters. One is a parameter of defects sensitivity, the second parameter is a threshold level and the third parameter is to identify the detected defects size and shape. The machine vision system has been successfully tested for the different types of defects on the surface of castings

A machine vision system for quality grading of painted slates

The major aim of this chapter is to detail the technology associated with a novel industrial inspection system that is able to robustly identify the visual defects present on the surface of painted slates. The development of a real-time automated slate inspection system proved to be a challenging task since the surface of the slate is painted with glossy dark colours, the slate is characterised by depth profile non-uniformities and it is transported at the inspection line via high-speed conveyors. In order to implement an industrial compliant system, in our design we had to devise a large number of novel solutions including the development of a full customised illumination set-up and the development of flexible image-processing procedures that can accommodate the large spectrum of visual defects that can be present on the slate surface and the vibrations generated by the slate transport system. The developed machine vision system has been subjected to a thorough robustness evaluation and the reported experimental results indicate that the proposed solution can be used to replace the manual procedure that is currently used to grade the painted slates in manufacturing environments

Variable illumination and invariant features for detecting and classifying varnish defects

This work presents a method to detect and classify varnish defects on wood surfaces. Since these defects are only partially visible under certain illumination directions, one image doesn\u27t provide enough information for a recognition task. A classification requires inspecting the surface under different illumination directions, which results in image series. The information is distributed along this series and can be extracted by merging the knowledge about the defect shape and light direction

Variable illumination and invariant features for detecting and classifying varnish defects

This work presents a method to detect and classify varnish defects on wood surfaces. Since these defects are only partially visible under certain illumination directions, one image doesn't provide enough information for a recognition task. A classification requires inspecting the surface under different illumination directions, which results in image series. The information is distributed along this series and can be extracted by merging the knowledge about the defect shape and light direction

Interior Materiality

The knowledge of materials and finishes is the bridge that links conceptual design to real-world application. It is among the core content of virtually all interior architecture/design curricula, moreover, access to up-to-date information on emerging technologies and trends is a key exigency for the contemporary designer. Accordingly, this book is authored to form a comprehensive resource for the “hows” and “whys” surrounding the functional and aesthetic contributions of a wide selection of materials and finishes used in multiple spatial design contexts. The knowledge base presented here is not only useful in shaping spatial experience, ensuring occupant well-being, and employing sustainable thinking but also beneficial in managing budget and schedule while enabling the delivery of top-quality work. The book investigates fundamental material properties, performance criteria, as well as sector-specific standards, regulations, and guidelines, with a special focus on concerns surrounding occupant health and safety as well as environmental impact and sustainability concerns. Furthermore, fabrication, installation, and maintenance issues were explored in detail. Various information collection and organization conventions are also discussed with regard to detailing, specification, estimation, and documentation of materials and finishes. The goals of the book can be listed as follows: ● Developing a vocabulary and knowledge base to comprehend and communicate concepts and paradigms associated with the history, classification, manufacturing, evaluation, fabrication, installation, and maintenance of materials and finishes. ● Identifying a broad range of materials and finishes, considering their aesthetic and performance properties, and understanding their utilization with regard to creative design intent, client expectations and requirements, user needs and experience, and incorporating life cycle implications. ● Providing a basis for achieving physical and psychological well-being for occupants, understanding the impact of changing social, cultural, economic, and ecological context, and eliminating negative environmental and social outcomes.https://newprairiepress.org/ebooks/1042/thumbnail.jp

Assessment, Diagnosis and Service Life Prediction

Service life prediction is crucial for the adoption of more sustainable solutions, allowing developers to optimize the costs and environmental impact of buildings during their life cycle. An accurate assessment of the service life of buildings requires a thorough understanding of the degradation mechanisms and behaviour of the construction materials. Building pathology assessment methods characterize the deterioration state of buildings, using specific measurable properties as indicators. Based on this information, different service life prediction methodologies can be defined to provide reliable data concerning the most probable failure time of whole buildings and individual components according to their characteristics and their age. This Special Issue provides new perspectives on the existing knowledge related with various aspects of the Assessment, Diagnosis and Service Life Prediction of buildings and their components. The ten original research studies published in this Special Issue result from research centres and university departments of Civil and Construction Engineering, Safety Management, Environmental Engineering, Geotechnical Engineering, and Architecture and the Built Environment, with relevant contributions from experts from Australia, Brazil, the Czech Republic, Hong Kong, Iran, Israel, Norway, Portugal, and Taiwan. The studies included in this Special Issue address topics related to: Building pathology assessment methods; Diagnosis of defects in buildings and components; Appropriate intervention and repair techniques; Deterministic and stochastic service life prediction models

A generic framework for colour texture segmentation

This thesis proposes a novel method to combine the colour and the texture for colour texture segmentation. The objective of this research work is to derive a framework for colour texture segmentation and to determine the contribution of colour in colour texture analysis. The colour texture processing is based on the feature extraction from colour-textured images. The texture features were obtained from the luminance plane along with the colour features from the chrominance planes. Based on the above mentioned approach, a method was developed for colour texture segmentation. The proposed method unifies colour and texture features to solve the colour texture segmentation problem. Two of the grey scale texture analysis techniques, Local Binary Pattern (LBP) and Discrete Cosine Transform (DCT) based filter approach were extended to colour images. An unsupervised fc-means clustering was used to cluster pixels in the chrominance planes. Non-parametric test was used to test the similarity between colour texture regions. An unsupervised texture segmentation method was followed to obtain the segmented image. The evaluation of the segmentation was based on the ROC curves. A quantitative estimation of colour and texture performance in segmentation was presented. The use of different colour spaces was also investigated in this study. The proposed method was tested using different mosaic and natural images obtained from VisTex and other predominant image database used in computer vision. The applications for the proposed colour texture segmentation method are, Irish Script On Screen (ISOS) images for the segmentation of the colour textured regions in the document, skin cancer images to identify the diseased area, and Sediment Profile Imagery (SPI) to segment underwater images. The inclusion of colour and texture as distributions of regions provided a good discrimination of the colour and the texture. The results indicated that the incorporation of colour information enhanced the texture analysis techniques and the methodology proved effective and efficient