{"id":4267,"date":"2024-05-27T08:32:26","date_gmt":"2024-05-27T13:32:26","guid":{"rendered":"https:\/\/elligno.com\/?page_id=4267"},"modified":"2024-05-29T09:32:08","modified_gmt":"2024-05-29T14:32:08","slug":"industrie-scierie-imagerie","status":"publish","type":"page","link":"https:\/\/elligno.com\/fr\/portfolio\/industrie-scierie-imagerie\/","title":{"rendered":"Industrie Scierie"},"content":{"rendered":"\n<h2 class=\"wp-block-heading\">Industrie Scierie (Imagerie)<\/h2>\n\n\n\n<h3 class=\"wp-block-heading\">D\u00e9tection par imagerie (vision)&nbsp;<\/h3>\n\n\n\n<p><strong>Projet <\/strong>programmation vision&nbsp;(imagerie)<\/p>\n\n\n\n<p><strong>Client<\/strong> Barrette-Chapais est un chef de file de l\u2019industrie foresti\u00e8re dans la production de bois de sciage au Qu\u00e9bec&nbsp;<\/p>\n\n\n\n<p><a href=\"https:\/\/barrettechapais.com\/\" target=\"_blank\" rel=\"noreferrer noopener\">Barette Chapais<\/a><\/p>\n\n\n\n<p><strong>Technologies<\/strong> C#, Halcon (librairie imagerie), .Net, programmation num\u00e9rique&nbsp;<\/p>\n\n\n\n<p><a href=\"https:\/\/www.mvtec.com\/products\/halcon\" target=\"_blank\" rel=\"noreferrer noopener\">librairie vision<\/a><\/p>\n\n\n\n<h3 class=\"wp-block-heading\">Projet (D\u00e9tection de la flache par imagerie&nbsp;)<\/h3>\n\n\n\n<p>Le d\u00e9fi majeur pour les scieries est l\u2019optimisation de la coupe des pi\u00e8ces de bois. La d\u00e9tection automatique des imperfections \u00e0 la surface d\u2019une pi\u00e8ce de bois est d\u2019une importance cruciale. La connaissance de la position des d\u00e9fauts est essentielle pour classer le bois selon les standards de qualit\u00e9 et d\u2019optimiser la coupe.&nbsp;&nbsp;&nbsp;<\/p>\n\n\n\n<h3 class=\"wp-block-heading\"><strong>Probl\u00e8me<\/strong>&nbsp;<\/h3>\n\n\n\n<p><strong>D\u00e9finition de la flache <\/strong>d\u00e9finie en fonction du plateau et des pentes, Image Repr\u00e9sentation de la pi\u00e8ce de bois par des pixels (intensit\u00e9 de l\u2019\u00e9chelle de gris donne l\u2019ordre de grandeur de l\u2019\u00e9paisseur), de blanc \u00e0 gris correspond respectivement \u00e0 l\u2019absence de bois \u00e0 la pleine \u00e9paisseur.&nbsp;<\/p>\n\n\n\n<p>Parmi les d\u00e9formations rencontr\u00e9es est celle de la d\u00e9tection de la flache. Les billots sont d&rsquo;abord coup\u00e9s en planches qui retiennent l&rsquo;\u00e9corce r\u00e9siduelle, appel\u00e9e flache, et d&rsquo;autres caract\u00e9ristiques ind\u00e9sirables (r\u00e9sidus) qui proviennent de la sciure ou autre et qui cache (masque) la vraie surface.<\/p>\n\n\n\n<p>Classification est bas\u00e9e sur la qualit\u00e9 et le grade du bois. La valeur est d\u00e9termin\u00e9e en utilisant une combinaison de la taille et de la qualit\u00e9 des planches. Cette t\u00e2che est habituellement effectu\u00e9e manuellement et est sujet \u00e0 des erreurs. En automatisant cette t\u00e2che qui est fastidieuse on minimise les erreurs qui peuvent \u00eatre couteuse en temps et argent.&nbsp;<\/p>\n\n\n\n<p><\/p>\n\n\n\n<h3 class=\"wp-block-heading\"><strong>Technologie par imagerie<\/strong><\/h3>\n\n\n\n<p>Mise au point d\u2019une application qui permet de d\u00e9tecter automatiquement les imperfections sur les pi\u00e8ces de bois en utilisant des techniques d\u2019imagerie (vision).&nbsp;<\/p>\n\n\n\n<p>L\u2019algorithme de d\u00e9tection de la flache se fait par des techniques de d\u00e9tection de contour (\u201c<em>edge detection<\/em>\u201d) emprunt\u00e9es \u00e0 l\u2019imagerie (vision).<\/p>\n\n\n\n<p>D\u00e9tection de la flache par imagerie :&nbsp; la technologie d\u2019images en niveaux (\u00e9chelle) de gris est utilis\u00e9e avec un syst\u00e8me de balayage de capture d\u2019images (profil) dans lesquelles chaque pixel repr\u00e9sente une mesure de l\u2019\u00e9paisseur de la pi\u00e8ce de bois.&nbsp; But est de localiser les endroits sur les bords de la pi\u00e8ce de bois qui contiennent des zones d\u2019imperfections. On applique des filtres (i.e. segmentation de l\u2019image en r\u00e9gions) pour extraire les images de profil telles que : m\u00e9diane, pente, plateau.&nbsp; \u00c0 partir de l\u2019analyse de ces images de profil, on est en mesure de localiser les zones o\u00f9 il y a des imperfections (par d\u00e9tection des bords).&nbsp;<\/p>\n\n\n\n<p><\/p>\n\n\n\n<h3 class=\"wp-block-heading\"><strong>Algorithme de traitement de l\u2019image (principales \u00e9tapes)<\/strong><\/h3>\n\n\n\n<p><\/p>\n\n\n\n<p>L\u2019algorithme est d\u00e9fini comme une s\u00e9quence d&rsquo;instructions qui op\u00e8rent sur un ensemble d&rsquo;images d&rsquo;entr\u00e9e (profils), transformant ces informations en une image de sortie int\u00e9ressante pour l&rsquo;utilisateur.&nbsp;<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Lecture du \u00ab scanner \u00bb transform\u00e9 en image (\u00e9chelle de gris)<\/li>\n\n\n\n<li>D\u00e9finir la r\u00e9gion-int\u00e9r\u00eat (ROI), enl\u00e8ve le noir de l\u2019image pour se concentrer sur la r\u00e9gion de bois<\/li>\n\n\n\n<li>Trouver le plateau (r\u00e9gion) et les r\u00e9gions de pente (faible \u00e0 forte) afin de d\u00e9terminer la flache<\/li>\n\n\n\n<li>Applique les filtres sur les diff\u00e9rentes r\u00e9gions) finalement le calcul de la flache<\/li>\n<\/ul>\n\n\n\n<h3 class=\"wp-block-heading\"><strong>Librairie de lissage pour la d\u00e9torsion de la pi\u00e8ce<\/strong>&nbsp;<\/h3>\n\n\n\n<p>Certaines pi\u00e8ces peuvent \u00eatre tordus (torsion, cambrure, courbure). Un algorithme de calcul num\u00e9rique est appliqu\u00e9 pour repr\u00e9senter les pi\u00e8ces sans la torsion et la cambrure.<\/p>\n\n\n\n<p>Bri\u00e8vement, la pi\u00e8ce est repr\u00e9sent\u00e9e par un \u2018<em>bounding box<\/em>\u2019, la cambrure et la torsion par des polyn\u00f4mes et on utilise un \u2018fit\u2019 pour trouver le centro\u00efde d\u00e9fini pour chaque section et une m\u00e9thode de lissage est effectu\u00e9 pour repr\u00e9senter la pi\u00e8ce droite.<\/p>\n\n\n\n<h4 class=\"wp-block-heading\">Appareiilage<\/h4>\n\n\n\n<p>L\u2019image de gauche montre le syst\u00e8me de vision pour balayage de la planche de bois. L&rsquo;image de droite on peut voir une coupe transversale repr\u00e9sentant les points fournis par le scanner (carte). Sur le bord, nous voyons une zone brune, ce qu&rsquo;on appelle la flache<\/p>\n\n\n\n<figure class=\"wp-block-gallery has-nested-images columns-default is-cropped wp-block-gallery-1 is-layout-flex wp-block-gallery-is-layout-flex\">\n<figure class=\"wp-block-image size-large\"><img loading=\"lazy\" decoding=\"async\" width=\"560\" height=\"252\" data-id=\"3720\" src=\"https:\/\/elligno.com\/wp-content\/uploads\/2022\/06\/ScannerApparitud.jpg\" alt=\"\" class=\"wp-image-3720\" srcset=\"https:\/\/elligno.com\/wp-content\/uploads\/2022\/06\/ScannerApparitud.jpg 560w, https:\/\/elligno.com\/wp-content\/uploads\/2022\/06\/ScannerApparitud-300x135.jpg 300w\" sizes=\"auto, (max-width: 560px) 100vw, 560px\" \/><\/figure>\n\n\n\n<figure class=\"wp-block-image size-large\"><img loading=\"lazy\" decoding=\"async\" width=\"800\" height=\"600\" data-id=\"3718\" src=\"https:\/\/elligno.com\/wp-content\/uploads\/2022\/06\/WanePicture.jpg\" alt=\"\" class=\"wp-image-3718\" srcset=\"https:\/\/elligno.com\/wp-content\/uploads\/2022\/06\/WanePicture.jpg 800w, https:\/\/elligno.com\/wp-content\/uploads\/2022\/06\/WanePicture-300x225.jpg 300w, https:\/\/elligno.com\/wp-content\/uploads\/2022\/06\/WanePicture-768x576.jpg 768w, https:\/\/elligno.com\/wp-content\/uploads\/2022\/06\/WanePicture-705x529.jpg 705w\" sizes=\"auto, (max-width: 800px) 100vw, 800px\" \/><\/figure>\n<\/figure>\n\n\n\n<p><\/p>\n\n\n\n<h3 class=\"wp-block-heading\">Application Graphique (GUI)<\/h3>\n\n\n\n<p>Le simulateur de flache est un outil qui permet de visualiser les diff\u00e9rentes r\u00e9gions (images de la segmentation). Aide pr\u00e9cieuse pour la validation sur des cas r\u00e9els.<\/p>\n\n\n\n<p>C\u2019est un petit simulateur qui permet de tester\/exp\u00e9rimenter diff\u00e9rents algorithmes de flache. A partir du GUI on peut ajuster certains param\u00e8tres de l\u2019algorithme de la flache et visualiser les effets&nbsp; A partir de l\u2019algorithme et de la repr\u00e9sentation de la pi\u00e8ce de bois (image dans ce cas-ci), on calcule la flache en termes de pixels et\/ou en termes d\u2019une r\u00e9gion,&nbsp;<\/p>\n\n\n\n<figure class=\"wp-block-gallery has-nested-images columns-default is-cropped wp-block-gallery-2 is-layout-flex wp-block-gallery-is-layout-flex\">\n<figure class=\"wp-block-image size-large\"><img loading=\"lazy\" decoding=\"async\" width=\"1024\" height=\"768\" data-id=\"3638\" src=\"https:\/\/elligno.com\/wp-content\/uploads\/2022\/05\/WaneImageFullWidth.jpg\" alt=\"\" class=\"wp-image-3638\" srcset=\"https:\/\/elligno.com\/wp-content\/uploads\/2022\/05\/WaneImageFullWidth.jpg 1024w, https:\/\/elligno.com\/wp-content\/uploads\/2022\/05\/WaneImageFullWidth-300x225.jpg 300w, https:\/\/elligno.com\/wp-content\/uploads\/2022\/05\/WaneImageFullWidth-768x576.jpg 768w, https:\/\/elligno.com\/wp-content\/uploads\/2022\/05\/WaneImageFullWidth-705x529.jpg 705w\" sizes=\"auto, (max-width: 1024px) 100vw, 1024px\" \/><\/figure>\n\n\n\n<figure class=\"wp-block-image size-large\"><img loading=\"lazy\" decoding=\"async\" width=\"1024\" height=\"768\" data-id=\"3637\" src=\"https:\/\/elligno.com\/wp-content\/uploads\/2022\/05\/SlopeImage.jpg\" alt=\"\" class=\"wp-image-3637\" srcset=\"https:\/\/elligno.com\/wp-content\/uploads\/2022\/05\/SlopeImage.jpg 1024w, https:\/\/elligno.com\/wp-content\/uploads\/2022\/05\/SlopeImage-300x225.jpg 300w, https:\/\/elligno.com\/wp-content\/uploads\/2022\/05\/SlopeImage-768x576.jpg 768w, https:\/\/elligno.com\/wp-content\/uploads\/2022\/05\/SlopeImage-705x529.jpg 705w\" sizes=\"auto, (max-width: 1024px) 100vw, 1024px\" \/><\/figure>\n<\/figure>\n\n\n\n<p><\/p>\n\n\n\n<h3 class=\"wp-block-heading\"><strong>Terminologie<\/strong>&nbsp;<\/h3>\n\n\n\n<p><strong>Flache <\/strong>un d\u00e9faut sur le bord de la pi\u00e8ce de bois par la pr\u00e9sence ou l\u2019absence de bois. La figure ci-dessous illustre les diff\u00e9rentes zones de flache d\u2019une pi\u00e8ce de bois.&nbsp;<\/p>\n\n\n\n<p><strong>Histogramme <\/strong>une m\u00e9thode pour analyser une image. L\u2019histogramme d\u2019une image tient le compte des fr\u00e9quences pour une couleur donn\u00e9e.&nbsp;<\/p>\n\n\n\n<p><strong>Image <\/strong>un tableau ou une matrice carr\u00e9e de pixels. Dans une image a 8-bits (\u00e9chelle de gris) chaque pixel a une intensit\u00e9 qui lui est assign\u00e9 de 0 \u00e0 255, appel\u00e9e tr\u00e8s souvent image noir et blanc (inclus plusieurs tons de gris)&nbsp;<\/p>\n\n\n\n<p><strong>Region-Of-Interest<\/strong> souvent appel\u00e9 ROI, est un sous-ensemble de l\u2019image compl\u00e8te. Obtenu apr\u00e8s avoir fait un traitement de l\u2019image. Par exemple l\u2019application d\u2019un filtre.&nbsp;<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Industrie Scierie (Imagerie) D\u00e9tection par imagerie (vision)&nbsp; Projet programmation vision&nbsp;(imagerie) Client Barrette-Chapais est un chef de file de l\u2019industrie foresti\u00e8re dans la production de bois de sciage au Qu\u00e9bec&nbsp; Barette Chapais Technologies C#, Halcon (librairie imagerie), .Net, programmation num\u00e9rique&nbsp; librairie vision Projet (D\u00e9tection de la flache par imagerie&nbsp;) Le d\u00e9fi majeur pour les scieries est [&hellip;]<\/p>\n","protected":false},"author":4,"featured_media":0,"parent":2885,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"class_list":["post-4267","page","type-page","status-publish","hentry"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v27.3 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>Industrie Scierie - Elligno<\/title>\n<meta name=\"description\" content=\"Application des techniques d\u2019imagerie (vision) dans l\u2019industrie du bois d\u2019\u0153uvre (scierie) pour la d\u00e9tection de la flache ou d\u00e9fauts.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/elligno.com\/fr\/portfolio\/industrie-scierie-imagerie\/\" \/>\n<meta property=\"og:locale\" content=\"fr_FR\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Industrie Scierie - 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