Document Classification with Prominent Objects

摘要

Systems and methods classify unknown documents in a group or not with reference document(s). Documents get scanned into digital images. Applying edge detection allows the detection of contours defining pluralities of image objects. The contours are approximated to a nearest polygon. Prominent objects get extracted from the polygons and derive a collection of features that together identify the reference document(s). Comparing the collection of features to those of an unknown image determine or not inclusion of the unknown with the reference(s). Embodiments typify collections of features, classification acceptance or not, application of algorithms, and imaging devices with scanners, to name a few.

主权项

1. In a computing system environment, a method for classifying whether or not an unknown input document belongs to a group with one or more reference documents, wherein digital images correspond to each of the unknown input document and the one or more reference documents, comprising:
applying edge detection to the digital images to detect contours of pluralities of image objects; approximating the contours of the image objects to a nearest polygon thereby defining pluralities of polygons; extracting prominent objects from one or more of the polygons to derive a collection of features that together identify the one or more reference documents; and comparing to the collection of features at least one prominent object from the digital image corresponding to the unknown input document to determine inclusion or not of the unknown input document with the one or more reference documents.