The fuzzy local-global duality in detecting pictorial patterns

Richardt, J.; Karl, F.; Müller, C. Catharina; Klette, Reinhard

doi:10.1016/0167-8655(95)00110-7

Cited by 5 publications

(2 citation statements)

References 8 publications

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“…These two scopes correspond to the local/global concept of the Fuzzy data analysis [12,13]. Therefore, in the first test series only the unfocussed beam is measured directly at the beam exit of the laser source.…”

Section: Experiments and Image Analysismentioning

confidence: 99%

<title>Intelligent beam monitoring and diagnostics for CO<formula><inf><roman>2</roman></inf></formula> lasers</title>

et al. 2001

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Changes in the laser beam quality caused by pollution, wasting or defects of the optical components and the laser beam source usually only can be detected by time-consumptive methods. Therefore a system is developed to automate and simplify the diagnosis of the laser beam radiation.As a solution a laser beam analyzer is permanently integrated into the laser system, an ergonomic user software is developed and the analyzer, the tooling-machine, and the laser are controlled by one computer.The user of a laser machine is enabled with this system to detect changes in the beam quality in an early state by daily measurements which are easy and fast to be carried out. Failures can be retraced to defects of the laser source, the beam guiding system, and the focussing optics by the use of image processing methods and fuzzy algorithms. Furthermore it is possible to detect stealing changes in the beam mode structure. Within the scope of quality assurance the data can be archived according to EN ISO 900x to be able to assign processing parameters to work-pieces.

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Section: Experiments and Image Analysismentioning

confidence: 99%

<title>Intelligent beam monitoring and diagnostics for CO<formula><inf><roman>2</roman></inf></formula> lasers</title>

et al. 2001

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“…The fuzzy C-means classification algorithms have also provided good results for image segmentation. These methods require a high computational cost [9] [10]. Ventriculograms are obtained from a medical imaging modality based on X-rays, after the injection of a contrast medium in the cavities of the heart aiming to enhance the contrast with respect to other tissues.…”

Section: Introductionmentioning

confidence: 99%

A Clustering Based Approach for Automatic Image Segmentation: An Application to Biplane Ventriculograms

Bravo

Medina

Díaz

2006

Lecture Notes in Computer Science

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Abstract. This paper reports on an automatic method for ventricular cavity segmentation in angiographic images. The first step of the method consists in applying a linear regression model that exploits the functional relationship between the original input image and a smoothed version. This intermediate result is used as input to a clustering algorithm, which is based on a region growing technique. The clustering algorithm is a two stage process. In the first stage an initial segmentation is achieved using as input the result of the linear regression and the smoothed version of the input image. The second stage is intended for refining the initial segmentation based on feature vectors including the area, the gray-level average and the centroid of each candidate region. The segmentation method is conceptually simple and provides an accurate contour detection for the left ventricle cavity.

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Image Analysis and Computer Vision: 1996

Rosenfeld

1997

Computer Vision and Image Understanding

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The fuzzy local-global duality in detecting pictorial patterns

Cited by 5 publications

References 8 publications

<title>Intelligent beam monitoring and diagnostics for CO<formula><inf><roman>2</roman></inf></formula> lasers</title>

<title>Intelligent beam monitoring and diagnostics for CO<formula><inf><roman>2</roman></inf></formula> lasers</title>

A Clustering Based Approach for Automatic Image Segmentation: An Application to Biplane Ventriculograms

Image Analysis and Computer Vision: 1996

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