&lt;title&gt;Color machine vision system for process control in the ceramics industry&lt;/title&gt;

Marqués, José Antonio Peñaranda; Briones, Leoncio; Flórez, Jesús

doi:10.1117/12.281279

Cited by 12 publications

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“…Traditionally, this classification is done by means of an operator intervention, nevertheless the trend in last years is to automate this process. 2,3 The other possible solution in order to achieve uniformity is stated as a hypothesis in this paper. We have made the assumption that visual appearance of through-body porcelain tiles depends on two factors: (1) the colour of each kind of grain; and (2) the proportion of each kind of grain.…”

Section: Problem Statementmentioning

confidence: 97%

Colour and proportion of grains measurement in through-body porcelain tiles by means of image processing

Peñaranda

Flores

Corzo

et al. 2006

Journal of the European Ceramic Society

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Section: Problem Statementmentioning

confidence: 97%

Colour and proportion of grains measurement in through-body porcelain tiles by means of image processing

Peñaranda

Flores

Corzo

et al. 2006

Journal of the European Ceramic Society

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Surface Grading Using Soft Colour-Texture Descriptors

López

Valiente

Prats

2005

Lecture Notes in Computer Science

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Abstract. This paper presents a new approach to the question of surface grading based on soft colour-texture descriptors and well known classifiers. These descriptors come from global image statistics computed in perceptually uniform colour spaces (CIE Lab or CIE Luv). The method has been extracted and validated using a statistical procedure based on experimental design and logistic regression. The method is not a new theoretical contribution, but we have found and demonstrate that a simple set of global statistics softly describing colour and texture properties, together with well-known classifiers, are powerful enough to meet stringent factory requirements for real-time and performance. These requirements are on-line inspection capability and 95% surface grading accuracy. The approach is also compared with two other methods in the surface grading literature; colour histograms [1] and centile-LBP [8]. This paper is an extension and in-depth development of ideas reported in a previous work [11].

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A Machine Vision System for Quality Grading of Painted Slates

Ghita

Carew

Whelan

2012

Machine Vision Handbook

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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.

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<title>Color machine vision system for process control in the ceramics industry</title>

Cited by 12 publications

References 0 publications

Colour and proportion of grains measurement in through-body porcelain tiles by means of image processing

Colour and proportion of grains measurement in through-body porcelain tiles by means of image processing

Surface Grading Using Soft Colour-Texture Descriptors

A Machine Vision System for Quality Grading of Painted Slates

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