1. M. Manouvrier. Objets Similaires de Grande Taille dans les Bases de Données. PhD thesis, Université Paris IX Dauphine (France), Jan. 2000. Thèse de Doctorat en Informatique. (http://www.lamsade.dauphine.fr/~manouvri/sujet_these.html#PSTHESE)
   Abstract: This thesis deals with the problems of large object versions in databases. Images are large objects loosely structured. Quad-tree may encode them. In image processing, users need to store and manage efficiently images resulting of processing operations. All along the process, users may consider the created images as versions of an original image. In this thesis, a structure, called Generic Quad-Tree, store similar images. Two images are defined similar if, for both images, the quad-trees that encode them are similar, i.e. differ only for a relative small number of nodes. The Generic Quad-Tree optimizes the memory space of similar images and allows processing of operations on them, like images comparison, comparison of the same area in different images, or simultaneous updates in different images. Large objects highly structured obviously appear in OODBMS, for instance during the management of collections of objects or roots (set of object identifiers). Index structures, for instance B+ tree, often manage this kind of objects. In order to solve the redundancy problem of set versions or collection versions, we propose mechanisms to manage B+ tree versions. The proposed mechanisms optimize the management of this kind of objects and may be generalized to any index tree structure. Therefore, they apply to a large domain of applications and particularly Geographic Information Systems and datawarehouse domains.

   Keywords : database, index, large object loosely or highly structured, versions, storage optimization, image similarity, collection of objects.
   

   @PhdThesis{Man00,
   SCHOOL = {Universit\'{e} Paris IX Dauphine (France)},
   AUTHOR = {Manouvrier, M.},
   TITLE = {{Objets Similaires de Grande Taille dans les Bases de Donn{\'e}es}},
   note = {Th{\`e}se de {D}octorat en {I}nformatique},
   YEAR = {2000},
   month = {Jan.},
   abstract = {This thesis deals with the problems of large object versions in databases. Images are large objects loosely structured. Quad-tree may encode them. In image processing, users need to store and manage efficiently images resulting of processing operations. All along the process, users may consider the created images as versions of an original image. In this thesis, a structure, called Generic Quad-Tree, store similar images. Two images are defined similar if, for both images, the quad-trees that encode them are similar, i.e. differ only for a relative small number of nodes. The Generic Quad-Tree optimizes the memory space of similar images and allows processing of operations on them, like images comparison, comparison of the same area in different images, or simultaneous updates in different images. Large objects highly structured obviously appear in OODBMS, for instance during the management of collections of objects or roots (set of object identifiers). Index structures, for instance B+ tree, often manage this kind of objects. In order to solve the redundancy problem of set versions or collection versions, we propose mechanisms to manage B+ tree versions. The proposed mechanisms optimize the management of this kind of objects and may be generalized to any index tree structure. Therefore, they apply to a large domain of applications and particularly Geographic Information Systems and datawarehouse domains. 
    
   Keywords : database, index, large object loosely or highly structured, versions, storage optimization, image similarity, collection of objects.},
   URL = {http://www.lamsade.dauphine.fr/~manouvri/sujet_these.html#PSTHESE} 
   }

1. G. Jomier and W. Cellary. The Database Version Approach. Networking and Information Systems Journal, 3(1/2000):177--214, 2000. Hermes.
   

   @Article{JC00,
   author = {Jomier, G. and Cellary, W.},
   title = {The {Database Version Approach}},
   journal = {Networking and Information Systems Journal},
   volume = {3},
   number = {1/2000},
   year = {2000},
   pages= {177--214},
   note = {Hermes} 
   }

2. G. Jomier, M. Manouvrier, and M. Rukoz. Storage and Management of Similar Images. Journal of the Brazilian Computer Society (JBCS), 3(6):13--26, avril-mai 2000. (postscript)
   Abstract: Numerical images are becoming more and more important and an increasing emphasis on multimedia applications has resulted in large volumes of images. However, images need a large memory space to be stored, so their efficient storage and retrieval generate challenges to the database community. This paper proposes a new algorithm for an efficient storage of sets of images. It is based on a version approach used in databases. It shows how to store and operate on similar images; two images are defined as similar if the quad-trees encoding them have only few different nodes. A data structure called Generic Quad-Tree (GQT) is proposed. It optimizes the memory space required to store similar images and allows an efficient navigation among them. An Image Tree stores the ancestors and descendants of an image, like a version hierarchy. Using the Image Tree, the Generic Quad-Tree allows an image to share common parts with its ancestors and descendants. The GQT approach and some algorithms for reading, modifying or removing images from the Generic Quad-Tree are described. Examples using black and white images and gray scale images are presented.

   Keywords: Generic Quad-Tree, operations on quad-trees, image representation, image comparison, optimization of memory space, image processing application.
   

   @Article{JMR00,
   author = {Jomier, G. and Manouvrier, M. and Rukoz, M.},
   title = {{Storage and Management of Similar Images}},
   journal = {Journal of the Brazilian Computer Society (JBCS)},
   volume = {3},
   number = {6},
   pages = {13--26},
   year = {2000},
   month = {avril-mai},
   abstract = {Numerical images are becoming more and more important and an increasing emphasis on multimedia applications has resulted in large volumes of images. However, images need a large memory space to be stored, so their efficient storage and retrieval generate challenges to the database community. This paper proposes a new algorithm for an efficient storage of sets of images. It is based on a version approach used in databases. It shows how to store and operate on similar images; two images are defined as similar if the quad-trees encoding them have only few different nodes. A data structure called Generic Quad-Tree (GQT) is proposed. It optimizes the memory space required to store similar images and allows an efficient navigation among them. An Image Tree stores the ancestors and descendants of an image, like a version hierarchy. Using the Image Tree, the Generic Quad-Tree allows an image to share common parts with its ancestors and descendants. The GQT approach and some algorithms for reading, modifying or removing images from the Generic Quad-Tree are described. Examples using black and white images and gray scale images are presented. 
    
   Keywords: Generic Quad-Tree, operations on quad-trees, image representation, image comparison, optimization of memory space, image processing application.},
   postscript = {http://www.lamsade.dauphine.fr/bdgl/PS/GJMMMR_JBCS2000.ps} 
   }

1. G. Jomier, M.A Peerbocus, and J.B. Huntzinger. Visualizing the Evolution of Spatiotemporal Objects. In Proc. of 9th Inter. Symposium on Spatial Data Handling, Beijing (China), Aug. 2000.
   

   @InProceedings{JPH00,
   author = {Jomier, G. and Peerbocus, M.A and Huntzinger, J.B.},
   title = {Visualizing the Evolution of Spatiotemporal Objects},
   booktitle = {Proc. of 9th Inter. Symposium on Spatial Data Handling},
   year = {2000},
   address = {Beijing (China)},
   month = {Aug.} 
   }

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