Autor/Autorin: Darwish Saad
Received his Ph.D. degree from the Alexandria University,Egypt for a thesis in image mining and image deillegalscription technologies. His research interests include image processing, security technologies and database management. Since Feb. 2012, he has been an associate professor in Institute of Graduate Studies and Research (IGSR), Egypt.
With the grow of the Internet and rapid advances made in storage devices, non-standard data such as images and videos have grown significantly in size. Rich information is hidden in these data collections that are potentially useful in a wide range of applications and research. The process of discovering valuable information from image data termed image mining finds its sources in data mining, content-based image retrieval, image understanding and computer vision. Image deillegalscription constitutes the initial basis for the image mining. The ability to develop an efficient and effective image deillegalscription model has been a more and more interesting and challenging topic of research. This thesis focuses on new key technologies for building an effective image deillegalscription tool, namely transformation-based image deillegalscription scheme. This scheme combines wavelet transform to construct accurate data modeling, XML technology to implement a general storage system for any set of images, and ontology approach to produce an effective data mining tool in a unified framework. The aim is to achieve an image deillegalscription tool that allows a high level of flexibility in describing images.
With the grow of the Internet and rapid advances made in storage devices, non-standard data such as images and videos have grown significantly in size. Rich information is hidden in these data collections that are potentially useful in a wide range of applications and research. The process of discovering valuable information from image data termed image mining finds its sources in data mining, content-based image retrieval, image understanding and computer vision. Image deillegalscription constitutes the initial basis for the image mining. The ability to develop an efficient and effective image deillegalscription model has been a more and more interesting and challenging topic of research. This thesis focuses on new key technologies for building an effective image deillegalscription tool, namely transformation-based image deillegalscription scheme. This scheme combines wavelet transform to construct accurate data modeling, XML technology to implement a general storage system for any set of images, and ontology approach to produce an effective data mining tool in a unified framework. The aim is to achieve an image deillegalscription tool that allows a high level of flexibility in describing images.
Darwish, SaadReceived his Ph.D. degree from the Alexandria University,Egypt for a thesis in image mining and image deillegalscription technologies. His research interests include image processing, security technologies and database management. Since Feb. 2012, he has been an associate professor in Institute of Graduate Studies and Research (IGSR), Egypt.
Über den Autor
Received the Ph.D. degree from the Alexandria University for a thesis in image mining and deillegalscription.His research and professional interests include image processing, web engineering, security technologies and database management. He has published in journals and severed as TPC of a number of international conferences
Klappentext
With the grow of the Internet and rapid advances made in storage devices, non-standard data such as images and videos have grown significantly in size. Rich information is hidden in these data collections that are potentially useful in a wide range of applications and research. The process of discovering valuable information from image data termed image mining finds its sources in data mining, content-based image retrieval, image understanding and computer vision. Image deillegalscription constitutes the initial basis for the image mining. The ability to develop an efficient and effective image deillegalscription model has been a more and more interesting and challenging topic of research. This thesis focuses on new key technologies for building an effective image deillegalscription tool, namely transformation-based image deillegalscription scheme. This scheme combines wavelet transform to construct accurate data modeling, XML technology to implement a general storage system for any set of images, and ontology approach to produce an effective data mining tool in a unified framework. The aim is to achieve an image deillegalscription tool that allows a high level of flexibility in describing images.
