Langue: anglais
Edité par LAP Lambert Academic Publishing, 2012
ISBN 10 : 3659128007 ISBN 13 : 9783659128004
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Ajouter au panierTaschenbuch. Etat : Neu. Algorithms for Image Thresholding | Study of Robust Algorithm For Image Thresholding Based On 2D Tsallis Entropy | Mohamed A. El-Sayed | Taschenbuch | Englisch | LAP Lambert Academic Publishing | EAN 9783659128004 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.
Langue: anglais
Edité par LAP LAMBERT Academic Publishing, 2012
ISBN 10 : 3659128007 ISBN 13 : 9783659128004
Vendeur : Mispah books, Redhill, SURRE, Royaume-Uni
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Ajouter au panierPaperback. Etat : Like New. LIKE NEW. SHIPS FROM MULTIPLE LOCATIONS. book.
Langue: anglais
Edité par LAP Lambert Academic Publishing, 2012
ISBN 10 : 3659128007 ISBN 13 : 9783659128004
Vendeur : AHA-BUCH GmbH, Einbeck, Allemagne
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Ajouter au panierTaschenbuch. Etat : Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Thresholding is an important and effective step in almost all areas of image processing. It is a main tool in pattern recognition, image segmentation, edge detection and scene analysis. In this book, we talk about different applications of thresholding such as: acoustic signal processing, muscle activity detection in EMG signal analysis, optical character recognition and character image extraction, image thresholding of historical documents, color applications, non destructive testing applications,forest fire detection, medical imaging, biometric application, satellite imaging, and object detection. In this way, we present Histogram shape, clustering, entropy-based thresholding method and types of entropy. Also we discuss many thresholding algorithms such as: Algorithms based on attribute similarity, spatial thresholding methods, and locally adaptive thresholding methods. In addition, we present a thresholding technique based on 2D Tsallis entropy. The effectiveness of the proposed method is demonstrated by using examples from the real-world and synthetic images. The performance evaluation of the proposed technique in terms of the quality of the thresholded images are presented.