12. In a computer-based system, a method for automatically separating documents represented within a plurality of images by delineating document boundaries and identifying document types in accordance with classification rules, the method comprising: automatically generating classification rules that predict a document type or subdocument type for each of the plurality of images based on textual information and/or graphical information represented in each respective one of the plurality of images, wherein the classification rules are generated based on analyzing textual information and/or graphical information of a plurality of training images using one or more of: a probabilistic network; relational algebra; and machine learning techniques; obtaining the plurality of images; automatically categorizing a plurality of subdocument images into a plurality of predetermined categories based on analyzing textual infoiniation and/or image characteristics of each of the plurality of document images using the classification rules, wherein said step of automatically categorizing comprises: producing an output score for each subdocument image based on the analysis thereof using the classification rules, wherein each output score represents an estimated document type probability or a subdocument type probability; and using a graph search algorithm to determine an optimum categorization sequence from a plurality of possible categorization sequences for said plurality of subdocument images based on said output scores; automatically generating at least one identifier for identifying which of said plurality of subdocument images belongs to which of said plurality of predetermined categories; and separating subdocuments within the plurality of subdocument images from one another by either: electronically associating at least one computer-generated label with at least some of the plurality of subdocument images, each label corresponding to a different one of the plurality of categories and comprising one of the one or more identifiers generated for identifying which of the plurality of subdocument images belongs to which of the plurality of predetermined categories; or inserting one or more computer-generated separation pages between at least some of the plurality of subdocument images to delineate images belonging to different ones of the plurality of categories, each separation page comprising one of the one or more identifiers generated for identifying which of the plurality of subdocument images belongs to which of the plurality of predetermined categories; or both electronically associating the at least one computer-generated label with at least some of the plurality of subdocument images and inserting the one or more computer-generated separation pages between at least some of the plurality of subdocument images.
12. In a computer-based system, a method for automatically separating documents represented within a plurality of images by delineating document boundaries and identifying document types in accordance with classification rules, the method comprising: automatically generating classification rules that predict a document type or subdocument type for each of the plurality of images based on textual information and/or graphical information represented in each respective one of the plurality of images, wherein the classification rules are generated based on analyzing textual information and/or graphical information of a plurality of training images using one or more of: a probabilistic network; relational algebra; and machine learning techniques; obtaining the plurality of images; automatically categorizing a plurality of subdocument images into a plurality of predetermined categories based on analyzing textual infoiniation and/or image characteristics of each of the plurality of document images using the classification rules, wherein said step of automatically categorizing comprises: producing an output score for each subdocument image based on the analysis thereof using the classification rules, wherein each output score represents an estimated document type probability or a subdocument type probability; and using a graph search algorithm to determine an optimum categorization sequence from a plurality of possible categorization sequences for said plurality of subdocument images based on said output scores; automatically generating at least one identifier for identifying which of said plurality of subdocument images belongs to which of said plurality of predetermined categories; and separating subdocuments within the plurality of subdocument images from one another by either: electronically associating at least one computer-generated label with at least some of the plurality of subdocument images, each label corresponding to a different one of the plurality of categories and comprising one of the one or more identifiers generated for identifying which of the plurality of subdocument images belongs to which of the plurality of predetermined categories; or inserting one or more computer-generated separation pages between at least some of the plurality of subdocument images to delineate images belonging to different ones of the plurality of categories, each separation page comprising one of the one or more identifiers generated for identifying which of the plurality of subdocument images belongs to which of the plurality of predetermined categories; or both electronically associating the at least one computer-generated label with at least some of the plurality of subdocument images and inserting the one or more computer-generated separation pages between at least some of the plurality of subdocument images. 18. The method of claim 12 , wherein at least some of the plurality of document images independently consist of a subdocument selected from a plurality of subdocuments, and the method comprising separating the subdocuments from a plurality of documents.