Industrial Image Processing

Demant, Christian; Streicher-Abel, Bernd; Waszkewitz, Peter

doi:10.1007/978-3-642-58550-0

Cited by 37 publications

(8 citation statements)

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“…The detection of this defect implies to enhance creases of an aluminium surface, which is seen through a plastic film. After testing several possibilities we found that the dark field illumination technique (Demant et al , 1999) based on red‐LEDs works pretty well. More specifically, we use three LED arrays organized as shown in Figure 3.…”

Section: System Designmentioning

confidence: 99%

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Real‐time quality control of surgical material packaging by artificial vision

López

Valveny

Villanueva

2005

Assembly Automation

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PurposeIn the last years, artificial vision systems have widely spread among quality control processes in many industries. In this paper we present an artificial vision system that automatically inspects sachets of surgical material in real‐time. These sachets are difficult to inspect by an artificial vision system due to high variability in their visual aspect and the material they are made of (aluminium and plastic) which can provoke a lot of reflections and shadows.Design/methodology/approachDue to variability of sachets and reflections in aluminium and plastic, the design of a good illumination system is very important for the success of the system. For that reason, we have used two sources of illumination, a dark field illumination and a diffuse frontal one, to avoid reflections and enhance important visual features. Moreover, the output of the system is not only the classification of the sachets as correct or defective, but it also identifies the sachet defect among the fifteen possible ones, a useful feature for just in time production. The proposed system is based on a PC modular and scalable architecture.FindingsThe system is currently working in actual production fulfilling the problem requirements with respect to false positive and false negative, in spite of the high variability of the product.Originality/valueThe system proposes two different kind of illumination systems to inspect difficult materials, such as plastic and aluminium, achieving good results. The proposed architecture of the system is modular and scalable and allows to increase computational power for visual tasks.

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Section: System Designmentioning

confidence: 99%

“…For this reason we decided to have another type of illumination. The most promising was based on diffuse front lighting (Demant et al , 1999). With very cheap components we have been able to make a system that satisfies our necessities.…”

Section: System Designmentioning

confidence: 99%

Real‐time quality control of surgical material packaging by artificial vision

López

Valveny

Villanueva

2005

Assembly Automation

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“…It is an emerging technology having verities of application in the field of space research, cinema, medical industry and machine vision. [1][2][3][4] Its growth has been fuelled by technological advances in digital imaging, computer processors and mass storage devices. Fields which traditionally used analogue imaging are now switching to digital systems, for their flexibility and affordability.…”

Section: Introductionmentioning

confidence: 99%

Application of image processing in mineral industry: a case study of ferruginous manganese ores

Singh¹,

Rao²

2006

Mineral Processing and Extractive Metallurgy

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The twenty-first century is bringing radical changes in mineral industry. High speed and low cost computational and sensing devices make it possible to reach at remote location and instantaneous control on the processes. Image processing which was very useful for some selected applications is getting popularity in mineral industry in changed scenario. In the present article image processing technique is explained briefly and its application in mineral industry has been summarised. A case study of ferruginous Indian manganese ore is presented. These ores show variation in their colour owing to variation in chemical composition. These ores were studied in red, green and blue colour space, histogram analysis; textural analysis and edge detection technique were used for separation of alumina lumps and to distinguish different ores. It shows acceptable results to carry out further studies for developing new cost effective ore blending and ore sorting methodologies for mineral industry. MATLAB 7 . 0 was used for image processing studies.

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“…These images were analyzed for 2D shape features, texture and color (Gonzalez and Woods, 1992; Sonka et al , 1999). The emerging technology of digital camera systems which use silicon based light sensors instead of films gives way to automated processing of images, broadening the range of possible applications to high‐volume surface analysis in production technology and quality control in the automotive industry (Demant et al , 1999; Rüther and Grabner, 2002).…”

Section: Introductionmentioning

confidence: 99%

In‐situmeasurement of dust deposition on bag filters using stereo vision and non‐rigid registration

Rüther

Saleem

Bischof

et al. 2005

Assembly Automation

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If you would like to write for this, or any other Emerald publication, then please use our Emerald for Authors service information about how to choose which publication to write for and submission guidelines are available for all. Please visit www.emeraldinsight.com/authors for more information. About Emerald www.emeraldinsight.comEmerald is a global publisher linking research and practice to the benefit of society. The company manages a portfolio of more than 290 journals and over 2,350 books and book series volumes, as well as providing an extensive range of online products and additional customer resources and services.Emerald is both COUNTER 4 and TRANSFER compliant. The organization is a partner of the Committee on Publication Ethics (COPE) and also works with Portico and the LOCKSS initiative for digital archive preservation. AbstractPurpose -The goal is to perform an in-situ measurement of dust layer thickness on bag filters. Design/methodology/approach -Presents a machine vision system in terms of hard-and software which is capable of obtaining the relative height difference of a cloth filter surface in different states of operation. The measurement process starts with a stereo reconstruction of filter surface patches. The patches are aligned to form a continuous model using the iterative closest point algorithm. Models acquired at different states of operation are registered using thin plate spline interpolation and afterwards subtracted from each other to obtain the relative height difference. Findings -Relative thickness measurement is possible with an accuracy ranging from 50 to 300 mm, depending on the operational states. Research limitations/implications -In-situ measurement of dust deposition is a new tool for examining the behaviour of commercial bag filters. Practical implications -Provides the foundation for a system measuring both thickness and density of dust deposition. Originality/value -Applies findings in the field of machine vision to a problem in process engineering and filter design.

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Industrial Image Processing

Cited by 37 publications

References 0 publications

Real‐time quality control of surgical material packaging by artificial vision

Real‐time quality control of surgical material packaging by artificial vision

Application of image processing in mineral industry: a case study of ferruginous manganese ores

In‐situmeasurement of dust deposition on bag filters using stereo vision and non‐rigid registration

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