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Segmentation par watershed

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Presentation sur la segmentation d'images par la méthode watershed
algorithme et exemple d'application
benouini rachid

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Segmentation par watershed

  1. 1. Segmentation par WATERSHED 1
  2. 2. Plan  Introduction  Notions théoriques  Exemple Applicatif en 3D  Algorithme Watershed ( LPE )  Conclusion 2
  3. 3. IntroductionMorphologie mathématique  L'algorithme de la ligne de partage des eaux (LPE) est un algorithme de segmentation d'images.  LPE utilise la description des images en termes géographiques.  LPE est définit comme étant une crête formant la limite entre deux bassins versants.  Une image est présentée comme un relief en associant un niveau de gris de chaque pixel à une altitude 3
  4. 4. La ligne de partage des eaux ( LPE ) Pour obtenir la LPE  Associer chaque valeur de pixel à une altitude.  Imaginer l’immersion d’un relief dans l’eau.  L’eau ne peut pénétrer dans les vallées que par ses minimas  LPE est représentée par les points où deux lacs disjoints se rejoignent au cours de l'immersion 4
  5. 5. La ligne de partage des eaux ( LPE ) LIGNEDEPARTAGEDESEAUX 5
  6. 6. EXEMPLE APPLICATIF Unity 3D Adobe Photoshop 6
  7. 7. EXEMPLE APPLICATIF – transformation en 3D 7
  8. 8. Algorithme Watershed ( LPE ): Vincent et Soille ENTÉES : Image I[N,M], Réel E pas d’altitude( tolérance ) SORTIE : Tableau d’entiers T[N,M] (avec T[x,y]= Etiquète de bassin ou Watershed ) DÉBUT MIN,HMAX : minimum et maximum global I, F : File d’attente (FIFO) Les pixels sont d’abord triés par ordre croissant d’altitude. (Ils sont ensuite traités par série : tous ceux entre h et h+E sont considérés d’altitude identique) Toute minima de l’image a un étiquète différente. POUR h DE MIN À HMAX On sélectionne les pixels du niveau [h,h+E]. On ajoute les pixels sélectionnées et qui touchent un bassin au file d’attente F POUR CHAQUE pixels P DU F On vois les 4 pixels adjacents de P et on met une étiquète dans la case qui correspond a P dans la table T (Voisin ou Watershed). Tous les pixels qui sont adjacents à P (+1) et sélectionnées sont ajouter a la fin F. FIN POUR On propage les étiquètes des bassin vers les pixels qui son étiqueté comme voisin. FIN POUR FIN 8
  9. 9. Algorithme Watershed ( LPE ): Exemple 9 10 50 10 10 30 50 70 50 10 30 30 10 20 60 60 0 20 50 60 70 10 70 10 50 30 30 20 50 60 20 30 40 10 20 60 20 40 0 20 50 30 50 10 50 60 70 60 50 40 10 50 10 10 30 50 70 50 10 30 30 10 20 60 60 0 20 50 60 70 10 70 10 50 30 30 20 50 60 20 30 40 10 20 60 20 40 0 20 50 30 50 10 50 60 70 60 50 40 10 50 10 10 30 50 70 50 10 30 30 10 20 60 60 0 20 50 60 70 10 70 10 50 30 30 20 50 60 20 30 40 10 20 60 20 40 0 20 50 30 50 10 50 60 70 60 50 40 10 50 10 10 30 50 70 50 10 30 30 10 20 60 60 0 20 50 60 70 10 70 10 50 30 30 20 50 60 20 30 40 10 20 60 20 40 0 20 50 30 50 10 50 60 70 60 50 40 10 50 10 10 30 50 70 50 10 30 30 10 20 60 60 0 20 50 60 70 10 70 10 50 30 30 20 50 60 20 30 40 10 20 60 20 40 0 20 50 30 50 10 50 60 70 60 50 40 10 50 10 10 30 50 70 50 10 30 30 10 20 60 60 0 20 50 60 70 10 70 10 50 30 30 20 50 60 20 30 40 10 20 60 20 40 0 20 50 30 50 10 50 60 70 60 50 40 10 50 10 10 30 50 70 50 10 30 30 10 20 60 60 0 20 50 60 70 10 70 10 50 30 30 20 50 60 20 30 40 10 20 60 20 40 0 20 50 30 50 10 50 60 70 60 50 40 10 50 10 10 30 50 70 50 10 30 30 10 20 60 60 0 20 50 60 70 10 70 10 50 30 30 20 50 60 20 30 40 10 20 60 20 40 0 20 50 30 50 10 50 60 70 60 50 40 10 50 10 10 30 50 70 50 10 30 30 10 20 60 60 0 20 50 60 70 10 70 10 50 30 30 20 50 60 20 30 40 10 20 60 20 40 0 20 50 30 50 10 50 60 70 60 50 40 10 50 10 10 30 50 70 50 10 30 30 10 20 60 60 0 20 50 60 70 10 70 10 50 30 30 20 50 60 20 30 40 10 20 60 20 40 0 20 50 30 50 10 50 60 70 60 50 40 Image original Minima en rouge Niveau MIN=0 Niveau 10 Niveau 20 Niveau 30 Création des lignes de partage Niveau 40 Niveau 50 Niveau 60 Niveau HMAX=70 Segmentation 4 connexité Watershed Non classifié E=10
  10. 10. Algorithme Watershed ( LPE ): Application 10
  11. 11. Algorithme Watershed ( LPE ):  Principe des marqueurs : ne considérer que certains minima  Le procédé de construction : on crée une image égale à l'originale et dans les zones d'intérêt on élimine les minima non voulues, on opère alors une LPE sur cette image modifiée.  Quand les minima sont remplacés par des marqueurs il est primordial de contrôler la place de ces marqueurs.  On peut créer des marqueurs manuellement. Mais le problème du choix automatique de marqueurs toujours existe.  Exemple de marqueur manuel : 11  Marqueur manuel
  12. 12. Algorithme Watershed ( LPE ) : Avantages et inconvénients  Avantages :  Grande précision sur les frontières obtenues  Distinction parfaite de 2 régions collées 12  Inconvénients :  Consommation de mémoire  Sensibilité au bruit  Sur-segmentation  Demande un post-traitement : Problèmes d’utilisation dans des systèmes temps réel.
  13. 13. Algorithme Watershed ( LPE ) : Améliorations  Plusieurs transformations possibles pour effectuer un prétraitement :  Filtrage : seuil, flou, érosion...  Pour suppression du bruit et suppression des minima à faible contraste pour minimiser la sur-segmentation  Transformation des données : Gradient, Inversion des niveaux, etc...  Mise en valeur des caractéristiques de l’image  Utilisation de Marqueurs pour choisir les zones d’intérêt 13
  14. 14. Conclusion  La segmentation d'images par l'algorithme de ligne de partage des eaux (Watershed en anglais) constitue un outil puissant pour analyser la topographie d’une image. Il a plusieurs implémentations Par Immersion « Vincent et Soille 1991 » et Par distances géodésiques « Meyer ».  Par ce qu’il n’existe pas de méthode de segmentation universelle. On devra adapter le processus de segmentation à chaque problématique.  Afin de pouvoir l'exploiter correctement, on doit effectue un prétraitement adéquat sur images à traiter pour éliminer toute information non significative soit éliminer certains contours non pertinents par filtrage ou améliorer sa luminosité, sa contraste ou autres. 14

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