9783845440552 - Image Retrieval Based on Content Using Color Feature: Color Image Processing and Retrieving di Afifi, Ahmed J.; Ashour, Wesam (6 risultati)

Taschenbuch. Condizione: Neu. Image Retrieval Based on Content Using Color Feature | Color Image Processing and Retrieving | Ahmed J. Afifi (u. a.) | Taschenbuch | 76 S. | Englisch | 2011 | LAP LAMBERT Academic Publishing | EAN 9783845440552 | Verantwortliche Person für die EU: BoD - Books on Demand, In de Tarpen 42, 22848 Norderstedt, info[at]bod[dot]de | Anbieter: preigu.

Paperback. Condizione: Like New. LIKE NEW. SHIPS FROM MULTIPLE LOCATIONS. book.

Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -In various application domains such as education, crime prevention, commerce, and biomedicine, the volume of digital data is increasing rapidly. The problem appears when retrieving the information from the storage media. Content-based image retrieval systems aim to retrieve images from large image databases similar to the query image based on the similarity between image features. This book presents a CBIR system that uses the color feature as a visual feature to represent the images. Images are selected from the WANG database that is widely used for CBIR performance evaluation. Ranklet Transform is used to make the image invariant to rotation and any image enhancement operations. For the resulting ranklet images, the color feature is extracted by calculating the color moments. The color moments are invariant to rotation and scaling. This is a benefit of our system. To speed up the retrieval time, images are clustered according to their features using k-means clustering algorithm. 76 pp. Englisch.

Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Afifi Ahmed J.Ahmed J. Afifi has graduated in 2008 with B.Sc. in Computer Engineering from Islamic University of Gaza. He has worked at IUG for 1 year as a teaching assistant. In 2011, he has graduated with M.Sc. in Computer Engineer.

Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -In various application domains such as education, crime prevention, commerce, and biomedicine, the volume of digital data is increasing rapidly. The problem appears when retrieving the information from the storage media. Content-based image retrieval systems aim to retrieve images from large image databases similar to the query image based on the similarity between image features. This book presents a CBIR system that uses the color feature as a visual feature to represent the images. Images are selected from the WANG database that is widely used for CBIR performance evaluation. Ranklet Transform is used to make the image invariant to rotation and any image enhancement operations. For the resulting ranklet images, the color feature is extracted by calculating the color moments. The color moments are invariant to rotation and scaling. This is a benefit of our system. To speed up the retrieval time, images are clustered according to their features using k-means clustering algorithm.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 76 pp. Englisch.

Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - In various application domains such as education, crime prevention, commerce, and biomedicine, the volume of digital data is increasing rapidly. The problem appears when retrieving the information from the storage media. Content-based image retrieval systems aim to retrieve images from large image databases similar to the query image based on the similarity between image features. This book presents a CBIR system that uses the color feature as a visual feature to represent the images. Images are selected from the WANG database that is widely used for CBIR performance evaluation. Ranklet Transform is used to make the image invariant to rotation and any image enhancement operations. For the resulting ranklet images, the color feature is extracted by calculating the color moments. The color moments are invariant to rotation and scaling. This is a benefit of our system. To speed up the retrieval time, images are clustered according to their features using k-means clustering algorithm.