Fast and efficient search method for graphical data
First Claim
1. In a guided search method employing low-to-high resolution techniques for locating any of one or more various types of relevant objects that may be represented in relatively high-resolution graphical data that occupies a given data domain Hn, where n≧
- 1;
wherein each type of relevant objects exhibits a different combination of one or more of multiple predetermined attributes;
the improvement comprising the step of employing high-to-low resolution techniques to prepare a search guide comprising a hierarchy of data arrays;
wherein;
a certain level of said hierarchy of data arrays comprises respective nodes that individually correspond to each of a plurality of data domains Hk-1 into which said given data domain Hn has been divided, each data domain Hk-1 being smaller than a data domain Hk, where 1≦
k≦
n and 0≦
(k-1)<
n;
another one of said data-tree node levels comprises at least one node that individually corresponds to a data domain Hk which is comprised a group of Hk-1 data domains;
a first attribute vector is stored in the node corresponding to each Hk-1 data domain, which first attribute vector abstracts all attribute information defined by the graphical data contained in that Hk-1 data domain; and
a second attribute vector, which pools the multiple attribute information stored by said first attribute vectors in all those nodes corresponding to the group of Hk-1 data domains that comprise each Hk data domain, stores information abstracted from that group of Hk-1 data domains in the node corresponding to that Hk data domain;
whereby a low-to-high resolution guided search may be made by employing the pooled abstracted multiple attribute information stored by the second attribute vector in a node corresponding to an Hk data domain to select the attribute information stored by the first attribute vector of at least one of the nodes corresponding to the Hk-1 data domains of the group that comprises that Hk data domain.
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Accused Products
Abstract
By processing the highest-resolution graphical data (e.g., image data) pertaining to relevant-objects defined by the graphical data into abstracted multiple-attribute information that is stored in a group of nodes of the lowest level of a hierarchy of data arrays (e.g., the leaf nodes of a complete data tree file), the present invention processes the data of each of these hierarchy of data arrays backward toward a single node of the highest level of the hierarchy of data arrays (e.g., the root node of a complete data tree file), to derive an attribute vector of all the abstracted multiple-attribute information at this single node. The derived attribute vector is then used to guide a search down the hierarchy of data arrays from the single node of its highest level toward at least a selected one of the group of nodes of its lowest level (which, by way of example, may correspond to the location of a likely relevant object). In this manner, a search made over a relatively large spatial domain for a relatively small relevant object can be converted into a search for the relevant object as described in the attribute domain of the hierarchy of data arrays, where such means as direct indexing may be used.
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Citations
12 Claims
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1. In a guided search method employing low-to-high resolution techniques for locating any of one or more various types of relevant objects that may be represented in relatively high-resolution graphical data that occupies a given data domain Hn, where n≧
- 1;
wherein each type of relevant objects exhibits a different combination of one or more of multiple predetermined attributes;
the improvement comprising the step of employing high-to-low resolution techniques to prepare a search guide comprising a hierarchy of data arrays;
wherein;a certain level of said hierarchy of data arrays comprises respective nodes that individually correspond to each of a plurality of data domains Hk-1 into which said given data domain Hn has been divided, each data domain Hk-1 being smaller than a data domain Hk, where 1≦
k≦
n and 0≦
(k-1)<
n;another one of said data-tree node levels comprises at least one node that individually corresponds to a data domain Hk which is comprised a group of Hk-1 data domains; a first attribute vector is stored in the node corresponding to each Hk-1 data domain, which first attribute vector abstracts all attribute information defined by the graphical data contained in that Hk-1 data domain; and a second attribute vector, which pools the multiple attribute information stored by said first attribute vectors in all those nodes corresponding to the group of Hk-1 data domains that comprise each Hk data domain, stores information abstracted from that group of Hk-1 data domains in the node corresponding to that Hk data domain; whereby a low-to-high resolution guided search may be made by employing the pooled abstracted multiple attribute information stored by the second attribute vector in a node corresponding to an Hk data domain to select the attribute information stored by the first attribute vector of at least one of the nodes corresponding to the Hk-1 data domains of the group that comprises that Hk data domain. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12)
- 1;
Specification