Image Processing of Edge and Surface Defects : Theoretical Basis of Adaptive Algorithms with Numerous Practical Applications
The edge and surface inspection is one of the most important and most challenging tasks in quality assessment in industrial production. Typical defects are cracks, inclusions, pores, surface flakings, partial or complete tears of material surface and s.o. These defects can occur through defective so...
שמור ב:
| מחבר ראשי: | |
|---|---|
| פורמט: | Livre numérique |
| שפה: | Anglais |
| יצא לאור: |
Berlin, Heidelberg :
Springer Berlin Heidelberg
[20..].
Cham : Springer Nature |
| מהדורה: | 1st ed. 2009. |
| סדרה: | Springer Series in Materials Science
123 |
| גישה מקוונת: | Accès sur la plateforme de l'éditeur Accès sur la plateforme Istex Accès Université d'Orléans Accès INSA CVL |
| הערה: |
Archives Springer e-books (Licence nationale) Archives Springer e-books (Licence nationale) |
| Autres localisations: | Voir dans le Sudoc |
| Edition sous un autre format: | • Image Processing of Edge and Surface Defects, Texte imprimé, 9783642007590 • Image processing of edge and surface defects, theoretical basis of adaptive algorithms with numerous practical applications, Roman Louban, Heidelberg, Springer, 2009, 1 vol. (XI-168 p.), Springer series in materials science, 978-3-642-00682-1 • Image Processing of Edge and Surface Defects, Texte imprimé, 9783642260353 |
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| 100 | 1 | |a Louban, Roman. | |
| 245 | 1 | 0 | |a Image Processing of Edge and Surface Defects : |b Theoretical Basis of Adaptive Algorithms with Numerous Practical Applications |c by Roman Louban. |
| 250 | |a 1st ed. 2009. | ||
| 260 | |a Berlin, Heidelberg : |b Springer Berlin Heidelberg. | ||
| 260 | |a Cham : |b Springer Nature, |c [20..]. | ||
| 490 | 0 | |a Springer Series in Materials Science |v 123 |x 2196-2812 | |
| 500 | |a Archives Springer e-books (Licence nationale) | ||
| 500 | |a Archives Springer e-books (Licence nationale) | ||
| 505 | 1 | |a Edge Detection Defect Detection on an Edge Defect Detection on an Inhomogeneous High-Contrast Surface Defect Detection on an Inhomogeneous Structured Surface Defect Detection in Turbo Mode Adaptive Edge and Defect Detection as a basis for Automated Lumber Classification and Optimisation Object Detection on Images Captured Using a Special Equipment Before an Image Processing System is Used. | |
| 506 | |a Accès en ligne pour les établissements français bénéficiaires des licences nationales | ||
| 506 | |a Accès soumis à abonnement pour tout autre établissement | ||
| 506 | |a Conditions particulières de réutilisation pour les bénéficiaires des licences nationales. https://www.licencesnationales.fr/springer-nature-ebooks-contrat-licence-ln-2017 | ||
| 520 | |a The edge and surface inspection is one of the most important and most challenging tasks in quality assessment in industrial production. Typical defects are cracks, inclusions, pores, surface flakings, partial or complete tears of material surface and s.o. These defects can occur through defective source material or through extreme strain during machining process. Detection of defects on a materialc surface can be complicated due to extremely varying degrees of material brightness or due to shadow areas, caused by the folding of the surface. Furthermore, impurities or surface discolourations can lead to artefacts that can be detected as pseudo-defects. The brightness conditions on the edge of material defects are interpreted as a Gauss distribution of a radiation and used for a physical model. Basing on this model, an essentially new set of adaptive edge-based algorithms was developed. Using these methods, different types of defects can be detected, without the measurements being dependent on local or global brightness conditions of the image taken. The new adaptive edge-based algorithms allow a defect detection on different materials, like metal, ceramics, plastics and stone. These methods make it possible to explicitly detect all kinds of different defects independently of their size, form and position and of the surface to be inspected. The adaptive edge-based methods provide a very wide spectrum of applications. | ||
| 776 | 0 | |t Image Processing of Edge and Surface Defects |b Texte imprimé |z 9783642007590 | |
| 776 | 0 | |0 13919374X |t Image processing of edge and surface defects |o theoretical basis of adaptive algorithms with numerous practical applications |f Roman Louban |c Heidelberg |n Springer |d 2009 |p 1 vol. (XI-168 p.) |s Springer series in materials science |z 978-3-642-00682-1 | |
| 776 | 0 | |t Image Processing of Edge and Surface Defects |b Texte imprimé |z 9783642260353 | |
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