Coarse document classification in an imaging device
View Patent ↗Systems and methods coarsely classify unknown documents in a group or not with reference document(s). Documents get scanned into digital images. Counts of contours are taken. The closer the counts of the contours of the unknown document reside to the reference document(s), the more likely the documents are all of a same type. Embodiments typify contour analysis, classification acceptance or not, application of algorithms, and imaging devices with scanners, to name a few.
1. In an imaging device having a scanned document input and a controller for executing instructions responsive thereto, a method for coarsely classifying whether or not an unknown input document belongs to a group with one or more reference documents, comprising:
receiving at the controller a scanned input from the scanned document input for each of the unknown input document and the one or more reference documents;
determining counts of contours of the scanned input for said each of the unknown input document and the one or more reference documents; and
determining inclusion or not in the group by comparing said counts of contours between images corresponding to the unknown input document and the one or more reference documents.
2. The method of claim 1 , further including scanning said each of the unknown input document and the one or more reference documents.
3. The method of claim 2 , wherein the scanning does not further initiate processing with optical character recognition.
4. The method of claim 1 , further including applying an algorithm with the controller including taking a difference of the counts of contours and dividing the difference by a maximum count of contours from either the unknown input document or the one or more reference documents.
5. The method of claim 1 , wherein the determining inclusion or not in the group further includes delineating a probability of acceptance for the counts of contours.
6. The method of claim 5 , further including coarsely classifying additional unknown documents relative to the unknown input document upon the determining inclusion or not in the group.
7. The method of claim 1 , wherein the determining counts of contours includes applying a same contour algorithm to said each of the unknown input document and the one or more reference documents.
8. The method of claim 1 , upon said determining inclusion or not in the group based on the counts of contours, adding or not the unknown input document to the one or more reference documents.
9. In an imaging device having a scanner and a controller for executing instructions responsive thereto, a method for coarsely classifying without OCR whether or not an unknown input document belongs to a group with one or more reference documents, comprising:
scanning each of the unknown input document and the one or more reference documents to form images thereof defined by pixels;
determining counts of contours in the images for said each of the unknown input document and the one or more reference documents;
delineating a probability of acceptance for inclusion or not in the group based on the determined counts of contours; and
determining said inclusion or not in the group based on the delineated probability of acceptance.
10. The method of claim 9 , further including applying an algorithm with the controller including taking a difference of the counts of contours and dividing the difference by a maximum count of contours from the images of either the unknown input document or the one or more reference documents.
11. The method of claim 10 , further including determining whether the applied algorithm results in a lower or higher value than the probability of acceptance.