The book aims to provide an understanding on how to segment the images based on active contour based model. Interactive image segmentation algorithms are sensitive to the user inputs and are often unable to produce an accurate boundary with a small amount of user interaction. They frequently rely on laborious user editing to refine the segmentation boundary. The Gaussian Mixture Model method for image segmentation exhibits many desirable properties of an effective interactive image segmentation algorithm, including robustness to user inputs and different initializations, the ability to produce a smooth and accurate boundary contour, and the ability to handle topology changes, it fails to handle semi-transparent images.The aim of this work is to extract sharp and steep images by handling semi-transparent images. An edge based active contour model has been proposed in which the image edge is extracted smoothly with the Greedy algorithm. Additionally Distance Regularized Level set Evolution algorithm has also been used to handle the very steep contour of the images. I personally thank my god, colleagues and parents for their encouragement and support for the publication.
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
Vendeur : BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Allemagne
Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -The book aims to provide an understanding on how to segment the images based on active contour based model. Interactive image segmentation algorithms are sensitive to the user inputs and are often unable to produce an accurate boundary with a small amount of user interaction. They frequently rely on laborious user editing to refine the segmentation boundary. The Gaussian Mixture Model method for image segmentation exhibits many desirable properties of an effective interactive image segmentation algorithm, including robustness to user inputs and different initializations, the ability to produce a smooth and accurate boundary contour, and the ability to handle topology changes, it fails to handle semi-transparent images.The aim of this work is to extract sharp and steep images by handling semi-transparent images. An edge based active contour model has been proposed in which the image edge is extracted smoothly with the Greedy algorithm. Additionally Distance Regularized Level set Evolution algorithm has also been used to handle the very steep contour of the images. I personally thank my god, colleagues and parents for their encouragement and support for the publication. 76 pp. Englisch. N° de réf. du vendeur 9786139889914
Quantité disponible : 2 disponible(s)
Vendeur : Revaluation Books, Exeter, Royaume-Uni
Paperback. Etat : Brand New. 76 pages. 8.66x5.91x0.18 inches. In Stock. N° de réf. du vendeur zk613988991X
Quantité disponible : 1 disponible(s)
Vendeur : moluna, Greven, Allemagne
Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Dhandapani RamyaHi, I am Ramya Dhandapani working as Assistant Professor in Tamilnadu, India. I am Passionate, self-motivated and committed. I focus to inculcate the pulse of growing demands in the Industry by conglomerating the stud. N° de réf. du vendeur 385876034
Quantité disponible : Plus de 20 disponibles
Vendeur : buchversandmimpf2000, Emtmannsberg, BAYE, Allemagne
Taschenbuch. Etat : Neu. This item is printed on demand - Print on Demand Titel. Neuware -The book aims to provide an understanding on how to segment the images based on active contour based model. Interactive image segmentation algorithms are sensitive to the user inputs and are often unable to produce an accurate boundary with a small amount of user interaction. They frequently rely on laborious user editing to refine the segmentation boundary. The Gaussian Mixture Model method for image segmentation exhibits many desirable properties of an effective interactive image segmentation algorithm, including robustness to user inputs and different initializations, the ability to produce a smooth and accurate boundary contour, and the ability to handle topology changes, it fails to handle semi-transparent images.The aim of this work is to extract sharp and steep images by handling semi-transparent images. An edge based active contour model has been proposed in which the image edge is extracted smoothly with the Greedy algorithm. Additionally Distance Regularized Level set Evolution algorithm has also been used to handle the very steep contour of the images. I personally thank my god, colleagues and parents for their encouragement and support for the publication.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 76 pp. Englisch. N° de réf. du vendeur 9786139889914
Quantité disponible : 1 disponible(s)
Vendeur : AHA-BUCH GmbH, Einbeck, Allemagne
Taschenbuch. Etat : Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - The book aims to provide an understanding on how to segment the images based on active contour based model. Interactive image segmentation algorithms are sensitive to the user inputs and are often unable to produce an accurate boundary with a small amount of user interaction. They frequently rely on laborious user editing to refine the segmentation boundary. The Gaussian Mixture Model method for image segmentation exhibits many desirable properties of an effective interactive image segmentation algorithm, including robustness to user inputs and different initializations, the ability to produce a smooth and accurate boundary contour, and the ability to handle topology changes, it fails to handle semi-transparent images.The aim of this work is to extract sharp and steep images by handling semi-transparent images. An edge based active contour model has been proposed in which the image edge is extracted smoothly with the Greedy algorithm. Additionally Distance Regularized Level set Evolution algorithm has also been used to handle the very steep contour of the images. I personally thank my god, colleagues and parents for their encouragement and support for the publication. N° de réf. du vendeur 9786139889914
Quantité disponible : 1 disponible(s)