1. In a document analysis system including a server, a method of enhancing electronic documents to improve automatic recognition and classification of the electronic documents, the method comprising: receiving, by the server, jobs containing job documents from a plurality of users, wherein each received job document is a binarized, one-bit-per-document-pixel image version of an original grayscale or color image source document; filtering, by the server, each page of the received binarized document to infer binarized background artifacts which result from the binarization of the original grayscale or color image source document and reside in the vicinity of binarized text and binarized image features in the page; distinguishing, by the server, the binarized text and binarized image features from the binarized background artifacts; extracting, by the server, the binarized text and binarized image features from the received binarized document; automatically recognizing and classifying, by the server, the received binarized document into a document category by using the extracted binarized text and binarized image features; organizing, by the server, each received job according to the document category of the corresponding job document; and removing, by the server, the binarized background artifacts, wherein the removal of the binarized background artifacts is performed after the binarized document image is inverted to white-on-black.
1. In a document analysis system including a server, a method of enhancing electronic documents to improve automatic recognition and classification of the electronic documents, the method comprising: receiving, by the server, jobs containing job documents from a plurality of users, wherein each received job document is a binarized, one-bit-per-document-pixel image version of an original grayscale or color image source document; filtering, by the server, each page of the received binarized document to infer binarized background artifacts which result from the binarization of the original grayscale or color image source document and reside in the vicinity of binarized text and binarized image features in the page; distinguishing, by the server, the binarized text and binarized image features from the binarized background artifacts; extracting, by the server, the binarized text and binarized image features from the received binarized document; automatically recognizing and classifying, by the server, the received binarized document into a document category by using the extracted binarized text and binarized image features; organizing, by the server, each received job according to the document category of the corresponding job document; and removing, by the server, the binarized background artifacts, wherein the removal of the binarized background artifacts is performed after the binarized document image is inverted to white-on-black. 15. The method of claim 1 further comprising comparing, by the server, the extracted binarized text and binarized image features with feature sets associated with each category of document.