Gamut selection in multi-engine systems
First Claim
1. A method for preparing to produce a multi-page document in a multi-engine system, the method comprising:
- identifying objects within the document;
identifying, by at least one component of the multi-engine system, characteristics of the identified objects, wherein identifying characteristics of the identified objects comprises identifying respective objects to be one of a graphic object, a pictorial object, a normal text or line object and a large text or line object;
selecting a respective target gamut for processing each respective identified object based upon at least the respective identified characteristics of the respective identified object, wherein selecting a respective target gamut comprises;
determining, for each identified large text or line object, pictorial object and/or graphic object, a similarity to other identified large text or line objects, pictorial objects and/or graphic objects in the document, thereby associating large text or line objects, pictorial objects and/or graphic objects in the document with groups of similar large text or line objects, pictorial objects and/or graphic objects,selecting an intersection of a respective plurality of gamuts, associated with the plurality of engines as a respective target gamut for respective groups of similar large text or line objects, pictorial objects and/or graphic objects having a group characteristic that meets a selected criteria; and
selecting a blended combination of a gamut of a selected individual engine and an intersection of a respective plurality of gamuts associated with the plurality of engines as a respective target gamut for a respective group of similar large text or line objects, pictorial objects and/or graphic objects having a group characteristic that does not meet the selected criteria;
wherein determining, for each identified large text or line object, pictorial object and/or graphic object, a similarity to other identified large text or line objects, pictorial objects and/or graphic objects in the document comprises at least one of;
identifying clusters of large text or line objects and/or graphic objects and sub-objects that have a same or nearly a same uniform color; and
identifying clusters of large text or line objects, pictorial objects and/or graphic objects and sub-objects that have the same or nearly the same combination or collection of colors.
1 Assignment
0 Petitions
Accused Products
Abstract
In preparation for rendering respective portions of a document via a respective plurality of engines, objects within the document are identified and characterized. A determination is made as to whether gamut variations between the engines might result in objectionable variations in the appearance of rendered versions of identified objects having similar characteristics. For those objects within the document for which the determination is made that variations might be objectionable, a target gamut is selected to be an intersection gamut of the engines to be used to render the document. For those objects within the document for which the determination is made that variations would be unobjectionable, the target gamut is selected to be that of selected individual engines. A system for selecting target gamuts for objects within a document can include an object identifier, a characteristic identifier and a gamut selector.
128 Citations
22 Claims
-
1. A method for preparing to produce a multi-page document in a multi-engine system, the method comprising:
-
identifying objects within the document; identifying, by at least one component of the multi-engine system, characteristics of the identified objects, wherein identifying characteristics of the identified objects comprises identifying respective objects to be one of a graphic object, a pictorial object, a normal text or line object and a large text or line object; selecting a respective target gamut for processing each respective identified object based upon at least the respective identified characteristics of the respective identified object, wherein selecting a respective target gamut comprises; determining, for each identified large text or line object, pictorial object and/or graphic object, a similarity to other identified large text or line objects, pictorial objects and/or graphic objects in the document, thereby associating large text or line objects, pictorial objects and/or graphic objects in the document with groups of similar large text or line objects, pictorial objects and/or graphic objects, selecting an intersection of a respective plurality of gamuts, associated with the plurality of engines as a respective target gamut for respective groups of similar large text or line objects, pictorial objects and/or graphic objects having a group characteristic that meets a selected criteria; and selecting a blended combination of a gamut of a selected individual engine and an intersection of a respective plurality of gamuts associated with the plurality of engines as a respective target gamut for a respective group of similar large text or line objects, pictorial objects and/or graphic objects having a group characteristic that does not meet the selected criteria;
wherein determining, for each identified large text or line object, pictorial object and/or graphic object, a similarity to other identified large text or line objects, pictorial objects and/or graphic objects in the document comprises at least one of;identifying clusters of large text or line objects and/or graphic objects and sub-objects that have a same or nearly a same uniform color; and identifying clusters of large text or line objects, pictorial objects and/or graphic objects and sub-objects that have the same or nearly the same combination or collection of colors. - View Dependent Claims (2, 3)
-
-
4. A method for preparing to produce a multi-page document in a multi-engine system, the method comprising:
-
identifying objects within the document; identifying, by at least one component of the multi-engine system, characteristics of the identified objects, wherein identifying characteristics of the identified objects comprises identifying respective objects to be one of a graphic object, a pictorial object, a normal text or line object and a large text or line object; and selecting a respective target gamut for processing each respective identified object based upon at least the respective identified characteristics of the respective identified object, wherein selecting a respective target gamut comprises; determining, for each identified large text or line object, pictorial object and/or graphic object, a similarity to other identified large text or line objects, pictorial objects and/or graphic objects in the document, thereby associating large text or line objects, pictorial objects and/or graphic objects in the document with groups of similar large text or line objects, pictorial objects and/or graphic objects; selecting an intersection of a respective plurality of gamuts, associated with the plurality of engines as a respective target gamut for respective groups of similar large text or line objects, pictorial objects and/or graphic objects having a group characteristic that meets a selected criteria; and selecting a blended combination of a gamut of a selected individual engine and an intersection of a respective plurality of gamuts associated with the plurality of engines as a respective target gamut for a respective group of similar large text or line objects, pictorial objects and/or graphic objects having a group characteristic that does not meet the selected criteria, wherein selecting the intersection of the respective plurality of gamuts, associated with the plurality of engines as the respective target gamut for respective groups of similar large text or line objects, pictorial objects and/or graphic objects having a group characteristic that meets the selected criteria comprises; selecting mapping to an intersection of a respective plurality of gamuts, associated with the plurality of engines, for respective groups of similar large text or line objects, pictorial objects and/or graphic objects having a group characteristic that meets the selected criteria in regard to at least one of a respective number of objects and sub-objects in the respective groups, a respective page-wise density of the objects and sub-objects in the respective groups throughout the document or a portion thereof, a respective size of the objects and sub-objects in the respective groups and a respective value of a respective function of one or more of the number, page-wise density and/or size. - View Dependent Claims (5, 6)
-
-
7. A method for preparing to produce a multi-page document in a multi-engine system, the method comprising:
-
identifying objects within the document; identifying by at least one component of the multi-engine system, characteristics of the identified objects, wherein identifying characteristics of the identified objects comprises identifying respective objects to be one of a graphic object, a pictorial object, a normal text or line object and a large text or line object; and selecting a respective target gamut for processing each respective identified object based upon at least the respective identified characteristics of the respective identified object, wherein selecting a respective target gamut comprises; determining, for each identified large text or line object, pictorial object and/or graphic object, a similarity to other identified large text or line objects, pictorial objects and/or graphic objects in the document, thereby associating large text or line objects, pictorial objects and/or graphic objects in the document with groups of similar large text or line objects, pictorial objects and/or graphic objects; selecting an intersection of a respective plurality of gamuts, associated with the plurality of engines as a respective target gamut for respective groups of similar large text or line objects, pictorial objects and/or graphic objects having a group characteristic that meets a selected criteria, and selecting a blended combination of a gamut of a selected individual engine and an intersection of a respective plurality of gamuts associated with the plurality of engines as a respective target gamut for a respective group of similar large text or line objects, pictorial objects and/or graphic objects having a group characteristic that does not meet the selected criteria, wherein determining, for each identified large text or line object, pictorial object and/or graphic object, a similarity to other identified large text or line objects, pictorial objects and/or graphic objects in the document comprises; identifying separate large text or line objects, pictorial objects, and graphic objects and sub-objects; analyzing the identified large text or line objects, pictorial objects, and graphic objects and subobjects through a use of histograms; and clustering, as similar, those large text or line objects, pictorial objects, and graphic objects and sub-objects that are associated with a same or similar histogram. - View Dependent Claims (8, 9)
-
-
10. A method for preparing to produce a multi-page document in a multi-engine system, the method comprising:
-
identifying respective objects within the document to have respective characteristics of being one of;
a graphic object, a pictorial object, a normal text or line object and a large text or line object; andselecting, by at least one component of the multi-engine system, a respective target gamut for processing each respective identified object based upon at least the respective identified characteristic of the respective identified object, the selected respective target gamut being one of;
a gamut of a selected individual engine, an intersection of a respective plurality of gamuts associated with the plurality of engines and a blended combination of a gamut of a selected individual engine and an intersection of a respective plurality of gamuts associated with the plurality of engines, the selecting being based upon at least the respective identified characteristics of the respective identified object, wherein selecting a respective target gamut comprises;determining, for each identified large text or line object, pictorial object and/or graphic object, a similarity to other identified large text or line objects, pictorial objects and/or graphic objects in the document, thereby associating large text or line objects, pictorial objects and/or graphic objects in the document with groups of similar large text or line objects, pictorial objects and/or graphic objects; selecting an intersection of a respective plurality of gamuts as the respective target gamut for respective groups of similar large text or line objects, pictorial objects and/or graphic objects having a group characteristic that meets a selected criteria; and selecting a blended combination of a gamut of a selected individual engine and an intersection of a respective plurality of gamuts associated with the plurality of engines as a respective target gamut for a respective group of similar large text or line objects, pictorial objects and/or graphic objects having a group characteristic that does not meet the selected criteria, wherein determining, for each identified large text or line object, pictorial object and/or graphic object, a similarity to other identified large text or line objects, pictorial objects and/or graphic objects in the document comprises at least one of; identifying clusters of large text or line objects and/or graphic objects and sub-objects that have a same or nearly a same uniform color; and identifying clusters of large text or line objects, pictorial objects and/or graphic objects and sub-objects that have the same or nearly the same combination or collection of colors. - View Dependent Claims (11, 12)
-
-
13. A method for preparing to produce a multi-page document in a multi-engine system, the method comprising:
-
identifying respective objects within the document to have respective characteristics of being one of;
a graphic object, a pictorial object, a normal text or line object and a large text or line object; andselecting, by at least one component of the multi-engine system, a respective target gamut for processing each respective identified object based upon at least the respective identified characteristic of the respective identified object, the selected respective target gamut being one of;
a gamut of a selected individual engine, an intersection of a respective plurality of gamuts associated with the plurality of engines and a blended combination of a gamut of a selected individual engine and an intersection of a respective plurality of gamuts associated with the plurality of engines, the selecting being based upon at least the respective identified characteristics of the respective identified object, wherein selecting a respective target gamut comprises;determining, for each identified large text or line object, pictorial object and/or graphic object, a similarity to other identified large text or line objects, pictorial objects and/or graphic objects in the document, thereby associating large text or line objects, pictorial objects and/or graphic objects in the document with groups of similar large text or line objects, pictorial objects and/or graphic objects; selecting an intersection of a respective plurality of gamuts as the respective target gamut for respective groups of similar large text or line objects, pictorial objects and/or graphic objects having a group characteristic that meets a selected criteria; and selecting a blended combination of a gamut of a selected individual engine and an intersection of a respective plurality of gamuts associated with the plurality of engines as a respective target gamut for a respective group of similar large text or line objects, pictorial objects and/or graphic objects having a group characteristic that does not meet the selected criteria, wherein selecting the intersection of a respective plurality of gamuts, associated with the plurality of engines, as the respective target gamut for respective groups of similar large text or line objects, pictorial objects and/or graphic objects having a group characteristic that meets the selected criteria comprises; selecting the intersection of the respective plurality of gamuts, associated with the plurality of engines, for respective groups of similar large text or line objects, pictorial objects and/or graphic objects having a group characteristic that meets the selected criteria in regard to at least one of;
a respective number of the objects and sub-objects in the respective groups, a respective page-wise density of the objects and sub-objects in the respective groups throughout the document or a portion thereof, a respective size of the objects and sub-objects in the respective groups and a respective value of a respective function of one or more of the number, page-wise density and/or size. - View Dependent Claims (14, 15)
-
-
16. A method for preparing to produce a multi-page document in a multi-engine system, the method comprising:
-
identifying respective objects within the document to have respective characteristics of being one of;
a graphic object, a pictorial object, a normal text or line object and a large text or line object; andselecting, by at least one component of the multi-engine system, a respective target gamut for processing each respective identified object based upon at least the respective identified characteristic of the respective identified object, the selected respective target gamut being one of;
a gamut of a selected individual engine, an intersection of a respective plurality of gamuts associated with the plurality of engines and a blended combination of a gamut of a selected individual engine and an intersection of a respective plurality of gamuts associated with the plurality of engines, the selecting being based upon at least the respective identified characteristics of the respective identified object, wherein selecting a respective target gamut comprises;determining, for each identified large text or line object, pictorial object and/or graphic object, a similarity to other identified large text or line objects, pictorial objects and/or graphic objects in the document, thereby associating large text or line objects, pictorial objects and/or graphic objects in the document with groups of similar large text or line objects, pictorial objects and/or graphic objects; selecting an intersection of a respective plurality of gamuts as the respective target gamut for respective groups of similar large text or line objects, pictorial objects and/or graphic objects having a group characteristic that meets a selected criteria; and selecting a blended combination of a gamut of a selected individual engine and an intersection of a respective plurality of gamuts associated with the plurality of engines as a respective target gamut for a respective group of similar large text or line objects, pictorial objects and/or graphic objects having a group characteristic that does not meet the selected criteria, wherein determining, for each identified large text or line object, pictorial object and/or graphic object, a similarity to other identified large text or line objects, pictorial objects and/or graphic objects in the document comprises; identifying separate large text or line objects, pictorial objects, and graphic objects and sub-objects; analyzing the identified large text or line objects, pictorial objects, and graphic objects and sub-objects through a use of histograms; clustering, as similar, those large text or line objects, pictorial objects, and graphic objects and sub-objects that are associated with a same or similar histogram. - View Dependent Claims (17, 18)
-
-
19. A document processing system comprising:
-
an object identifier that is operative to identify image objects within the document; a characteristic identifier that is operative to identify characteristics of the identified objects, wherein the characteristic identifier is operative to identify a respective object to be one of a graphic object, a pictorial object, a normal text or line object and a large text or line object; and a gamut selector that is operative to select a respective target gamut for processing each respective identified object based upon at least the respective identified characteristics of the respective identified object wherein the gamut selector is operative to select a respective target gamut by determining, for each identified large text or line object, pictorial object and/or graphic object, a similarity to other identified large text or line object, pictorial object and/or graphic objects in the document, thereby associating large text or line objects, pictorial objects and/or graphic objects in the document with groups of similar large text or line objects, pictorial objects and/or graphic objects, selecting an intersection of a respective plurality of gamuts, associated with the plurality of engines, as the respective target gamut for respective groups of similar large text or line objects, pictorial objects and/or graphic objects having a group characteristic that meets the selected criteria and selecting at least one individual engine gamut of at least one selected engine as the at least one respective target gamut for respective groups of similar large text or line objects, pictorial objects and/or graphic objects having a group characteristic that does not meet the selected criteria and wherein the gamut selector is operative to determine the similarity, for each identified large text or line object, pictorial object and/or graphic object, a similarity to other identified large text or line objects, pictorial objects and/or graphic objects by at least one of identifying clusters of large text or line objects, pictorial objects and/or graphic objects and sub-objects that have a same or nearly a same uniform color and identifying clusters of large text or line objects, pictorial objects and/or graphic objects and sub-objects that have a same or nearly a same combination or collection of colors. - View Dependent Claims (20)
-
-
21. A document processing system comprising:
-
an object identifier that is operative to identify image objects within the document a characteristic identifier that is operative to identify characteristics of the identified objects, wherein the characteristic identifier is operative to identify a respective object to be one of a graphic object, a pictorial object, a normal text or line object and a large text or line object; and a gamut selector that is operative to select a respective target gamut for processing each respective identified object based upon at least the respective identified characteristics of the respective identified object wherein the gamut selector is operative to select a respective target gamut by determining, for each identified large text or line object, pictorial object and/or graphic object, a similarity to other identified large text or line object, pictorial object and/or graphic objects in the document, thereby associating large text or line objects, pictorial objects and/or graphic objects in the document with groups of similar large text or line objects, pictorial objects and/or graphic objects, selecting an intersection of a respective plurality of gamuts, associated with the plurality of engines, as the respective target gamut for respective groups of similar large text or line objects, pictorial objects and/or graphic objects having a group characteristic that meets the selected criteria and selecting at least one individual engine gamut of at least one selected engine as the at least one respective target gamut for respective groups of similar large text or line objects, pictorial objects and/or graphic objects having a group characteristic that does not meet the selected criteria and wherein the gamut selector is operative to select an intersection of a respective plurality of gamuts, associated with the plurality of engines, as the respective target gamut for respective groups of similar large text or line objects, pictorial objects and/or graphic objects having a group characteristic that meets the selected criteria in regard to at least one of a respective number of the large text or line objects, pictorial objects and/or graphic objects and sub-objects in the respective groups, a respective page-wise density of the large text or line objects, pictorial objects and/or graphic objects and sub-objects in the respective groups throughout the document or a portion thereof, a respective size of the large text or line objects, pictorial objects and/or graphic objects and sub-objects in the respective groups and a respective value of a respective function of one or more of the number, page-wise density and/or size.
-
-
22. A document processing system comprising:
-
an object identifier that is operative to identify image objects within the document; a characteristic identifier that is operative to identify characteristics of the identified objects, wherein the characteristic identifier is operative to identify a respective object to be one of a graphic object, a pictorial object, a normal text or line object and a large text or line object; and a gamut selector that is operative to select a respective target gamut for processing each respective identified object based upon at least the respective identified characteristics of the respective identified object wherein the gamut selector is operative to select a respective target gamut by determining, for each identified large text or line object, pictorial object and/or graphic object, a similarity to other identified large text or line object, pictorial object and/or graphic objects in the document, thereby associating large text or line objects, pictorial objects and/or graphic objects in the document with groups of similar large text or line objects, pictorial objects and/or graphic objects, selecting an intersection of a respective plurality of gamuts, associated with the plurality of engines, as the respective target gamut for respective groups of similar large text or line objects, pictorial objects and/or graphic objects having a group characteristic that meets the selected criteria and selecting at least one individual engine gamut of at least one selected engine as the at least one respective target gamut for respective groups of similar large text or line objects, pictorial objects and/or graphic objects having a group characteristic that does not meet the selected criteria, wherein the gamut selector is operative to select an individual engine target gamut for the object, if the object is identified as a normal text or line object and wherein the gamut selector is operative to determine, for each identified large text or line objects, pictorial objects and/or graphic objects and sub-objects, a similarity to other identified large text or line objects, pictorial objects and/or graphic objects and sub-objects in the document by identifying separate large text or line objects, pictorial objects, and graphic objects and sub-objects, analyzing the identified large text or line objects, pictorial objects, and/or graphic objects and sub-objects through a use of histograms, and clustering as similar, those large text or line objects, pictorial objects, and graphic objects and sub-objects that are associated with a same or similar histogram.
-
Specification