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Un filtre de Gabor est un filtre linéaire dont la réponse impulsionnelle est une sinusoïde modulée par une fonction gaussienne (également appelée ondelette de Gabor). Il porte le nom du physicien anglais d'origine hongroise Dennis Gabor.
Gabor, Filtre de
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Un filtre de Gabor est un filtre linéaire dont la réponse impulsionnelle est une sinusoïde modulée par une fonction gaussienne (également appelée ondelette de Gabor). Il porte le nom du physicien anglais d'origine hongroise Dennis Gabor.
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Fabric defect detection based on golden image subtraction / Jun-Feng Jing in COLORATION TECHNOLOGY, Vol. 133, N° 1 (02/2017)
[article]
Titre : Fabric defect detection based on golden image subtraction Type de document : texte imprimé Auteurs : Jun-Feng Jing, Auteur ; Shan Chen, Auteur ; Peng-Fei Li, Auteur Année de publication : 2017 Article en page(s) : p. 26–39 Note générale : Bibliogr. Langues : Anglais (eng) Catégories : Gabor, Filtre de Un filtre de Gabor est un filtre linéaire dont la réponse impulsionnelle est une sinusoïde modulée par une fonction gaussienne (également appelée ondelette de Gabor). Il porte le nom du physicien anglais d'origine hongroise Dennis Gabor.
Imagerie (technique)
Textiles et tissus -- DéfautsIndex. décimale : 667.3 Teinture et impression des tissus Résumé : To realise the universality and practicality of fabric defect detection in the textile industry, this paper proposes two approaches based on the Gabor filter and the golden image subtraction method. A method known as Gabor preprocessed golden image subtraction is first introduced, which filters a test fabric image by the real component of the Gabor filter with a 1 Hz centre frequency and a 90° angle. Golden image subtraction performs subtractions between the golden template and the filtered image to obtain a resultant image, and the segmentation threshold is determined by the direct threshold. The second method is Gabor preprocessed golden image subtraction based on a genetic algorithm, which can automatically select the parameter groups of the Gabor filter via the genetic algorithm. In addition, the paper also presents an extensive comparison between the proposed methods and wavelet preprocessed golden image subtraction. Meanwhile, the performances of the aforementioned three methods are tested in a real machine vision detection system to meet the actual demands of the textile industry. It can be concluded that Gabor preprocessed golden image subtraction provides the best detection results. The overall detection success rate is 95.62%, with 80 defect-free images and 80 defective images for fabric textures of common types. Note de contenu : - EXPERIMENTAL : Image processing theories - GIS based on Gabor filter - Parameter tuning
- RESULTS AND DISCUSSION : Machine vision system - Experimental materials - Results of GGIS and GAGIS - Comparison with WGISDOI : 10.1111/cote.12239 En ligne : https://drive.google.com/file/d/1HyYoUkencCMWErVOxOZXXPmJ97lnuzbD/view?usp=drive [...] Format de la ressource électronique : Permalink : https://e-campus.itech.fr/pmb/opac_css/index.php?lvl=notice_display&id=27877
in COLORATION TECHNOLOGY > Vol. 133, N° 1 (02/2017) . - p. 26–39[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 18636 - Périodique Bibliothèque principale Documentaires Disponible The design of optimal real gabor filters and their applications in fabric defect detection / Zehong Chen in COLORATION TECHNOLOGY, Vol. 131, N° 4 (08/2015)
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Titre : The design of optimal real gabor filters and their applications in fabric defect detection Type de document : texte imprimé Auteurs : Zehong Chen, Auteur ; Xiaoxia Feng, Auteur Année de publication : 2015 Article en page(s) : p. 279-287 Note générale : Bibliogr. Langues : Anglais (eng) Catégories : Détection de défauts (Ingénierie)
Gabor, Filtre deUn filtre de Gabor est un filtre linéaire dont la réponse impulsionnelle est une sinusoïde modulée par une fonction gaussienne (également appelée ondelette de Gabor). Il porte le nom du physicien anglais d'origine hongroise Dennis Gabor.
Textiles et tissus -- DéfautsIndex. décimale : 667.3 Teinture et impression des tissus Résumé : Fabric defect detection has been recognised as one of the key challenges for automatic production, and Gabor filters are one of the most useful tools in detecting fabric defects. The half-peak tangent method is applied in real Gabor filter design so that the filters can cover the frequency of defects as much as possible. Meanwhile, the half-peak-magnitude contours of the neighbouring filters are tangential. On this basis, two optimal orientations are selected by applying direction masks, and the optimal scale at each optimal orientation is determined according to the signal-to-noise ratio. In this way, two optimal real Gabor filters are obtained. A new algorithm based on the two optimal filters is proposed for fabric defect detection. A series of experiments are carried out for 46 fabric defect images combined with 46 corresponding reference fabric images, in order to verify the effectiveness of the new algorithm. The experimental results obtained show that the new algorithm can accurately detect defects in grey fabric defect images as well as in colour images. For the 46 fabric defect images, the detection rate is 95.66%, indicating that the new algorithm performs well. In addition, comparison of the new algorithm with other algorithms in the literature demonstrates that the new algorithm is more effective in the detection of several fabric defect images. Note de contenu : - RELATED THEORIES OF GABOR FILTERS
- THE DESIGN OF REAL GABOR FILTERS WITH MULTIPLE SCALES AND MULTIPLE ORIENTATIONS : Determining the orientation angles of real gabor filters - Determining the standard deviations of real gabor filters - Determining the radial frequencies of real gabor filters
- OBTAINING TWO OPTIMAL REAL GABOR FILTERS FOR FABRIC DEFECT DETECTION : Detection the optimal orientations of real gabor filters by direction masks - Determining the corresponding optimal scales by the signal-to-noise ratio
- A NEW ALGORITHM BASED ON THE TWO REAL GABOR FILTERS FOR FABRIC DEFECT DETECTION
- A SERIES OF EXPERIMENTS APPLYING THE NEW ALGORITHM : Detecting defects in grey fabric images by the new algorithm - Detecting defects in colour fabric images by the new algorithm - Comparing the new algorithm with other algorithmDOI : 10.1111/cote.12154 En ligne : https://onlinelibrary.wiley.com/doi/epdf/10.1111/cote.12154 Format de la ressource électronique : Permalink : https://e-campus.itech.fr/pmb/opac_css/index.php?lvl=notice_display&id=24427
in COLORATION TECHNOLOGY > Vol. 131, N° 4 (08/2015) . - p. 279-287[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 17353 - Périodique Bibliothèque principale Documentaires Disponible