Xerox Corporation

Mike C Chen

Zhigang Fan

John W Wu

Kien A Phong

Felice A Micco

A method and apparatus for preventing or inhibiting effective reproduction of documents such as currency, checks, stock certificates, and any other printed document including a pre-defined security mark printed therein. The subject method and apparatus operate to effect a multi-step review of all digital image data acquired from a printed document to be reproduced for purposes of locating any potential security marks and further examining same for purposes of positively identifying a potential security mark as an actual security mark. If a mark is located and verified to be an authentic security mark, effective reproduction of the printed document will not be permitted and/or other security measures will be taken. A pretest of a mark consists of deleting the fine line patterns that may be printed on top of the mark by smoothing the data in an averaging process, and then determining the difference between the density of the darkest and lightest pixels in the area. A difference smaller than a predetermined value means that the mark is not valid.

Digital imaging method and apparatus for detection of document security marks

This algorithm is a method for resizing and resampling an image in one step. In the vertical, process or slow scan, direction, from the resampling ratio and from the image size variation, an algorithm can compute where, on the page, the scan lines may be deleted. For a numerical example, if the input is 400 pixels per unit time, resampling of four to one would yield one scan line every {fraction (1/100)} of a unit. If, in addition, the image has to be reduced by 5%, then the final output would be one scan line every {fraction (1/95)},of a time unit. This algorithm accomplishes this result by using a running sum of error terms. Simply stated, if it is known that the previous output scan was output at exactly the right time, the error is zero, but if the scan was output too soon or too late, there will be an error term. For each new scan that is now output, {fraction (1/400)},of a time unit is added to the error term. Finally, when the error term rises to a predetermined threshold, then the algorithm knows that that is the closest approximation that can be made, the current scan line is output, {fraction (1/95)},of a time unit is subtracted from the running sum, and the algorithm proceeds to the next scans.

Anti-counterfeit detection method

An anti-counterfeit currency detection method is disclosed wherein local edge information is utilized for accurately detecting lines and curves of legitimate notes. The method can more accurately determine the location and orientation of a pattern and thus provides more reliable currency detection. A detector is trained off-line with example notes resulting in a stored template generated by recording a test pattern similar to a pattern to be tested; anchor lines are identified within said template which are further represented in subsequent test patterns. The template is rotated and shifted before matching it to the test pattern so that anchor lines align with long lines detected within the test pattern. The template and test pattern are then compared to determine whether there is a match. The system comprises a microprocessor is programmed to facilitate the training of a detector off-line with example notes which are scanned into said system wherein a template is generated by recording an image pattern of said example notes similar to a test pattern to be detected. The microprocessor identifies anchor lines within the template which are further represented in said test pattern; rotates and shifts the template before matching it to the test pattern so that anchor lines align with lines which may be detected within said test pattern; and compares the template to the test pattern to determine whether said anchor lines exist within said test pattern.

Method for counterfeit currency detection using orthogonal line comparison

A currency detection method that detects seals on currency in order to prevent printing and defeat counterfeiting. Seal patterns are detected. The detector has the ability to identify whether an image contains one or several pre-selected seal patterns. The detection is rotational and shift invariant--a suspect mark can be in any orientation and at any location within a tested image. With the method: a detector is trained off-line with distinctive marks resulting in templates which are generated and recorded for each of the distinctive; sample images bearing suspect marks are received by the detector and the location and orientation of the suspect marks are identified; the templates are rotated and shifted for alignment of the templates to the suspect marks; the templates and the suspects marks are compared to determine whether there is a match. A microprocessor is programmed to become familiarzed with a plurality of distinctive marks through training and to analyze and detect seals within tested documents. A memory stores the marks as templates. A scanner may be used with the system during training and detection to capture marks and tested images bearing marks for use by the system. The resulting output can be used by controlled systems, such as copiers and scanners, to suspend further action on documents where counterfeiting is suspected.

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Cerritos, CA, United States of America

Mike C Chen