Banctec, Incorporated

Cynthia D Ott

David Michael Ott

A color scanning technique that maintains a high image quality while permitting improved scanning speed and improved perceived resolution. A color pixel array and a luminance pixel array are generated representative of a target object. The pixel arrays are related in that one or more luminance pixels of the luminance pixel array cover each pixel of the color pixel array. A luminance value is sensed for each luminance pixel, and three primary color values are sensed for each color pixel. A measured luminance value is then associated with each respective color pixel wherein the measured luminance value is a function of the sensed luminance values for the one or more luminance pixels covering the respective color pixel. A derived luminance value is also calculated for each respective color pixel wherein the derived luminance value is a function of the three sensed primary color values for the respective color pixel. A luminance correction factor is then determined for each respective color pixel as a function of the color pixel's derived and measured luminance values. The luminance correction factor for each respective color pixel is applied to the sensed primary color values of the color pixel, or to a linear combination thereof, to determine luminance-corrected color values. In this way the overall pixel luminance implied by the aggregate measured color values will show a consistency with the directly measured luminances. The luminance-corrected color values together with the measured luminance values may then be subjected to further appropriate transformation to determine color coordinates for each luminance pixel and/or for each color pixel, which may then be used in further processing. A logarithmic method is used for efficient computation of correction factors and luminance-corrected color values.

Luminance correction for color scanning using a measured and derived luminance value

Digital images of documents such as bank checks are analyzed to determine acceptable image quality by capturing an image at a first or normal sensitivity and at a second or greater sensitivity. Both sets of image signals are subjected to speckle filtering to remove extraneous image elements or noise. The greater sensitivity signals are grouped in discrete areas having a predetermined number of pixels and black pixels which are connected are identified as an object in each discrete area. Each object is analyzed by measuring height, width, area, perimeter, aspect ratio, density ratio and perimeter to area ratio. Predetermined limits for these characteristics are applied to each object to classify the object as stroke-like or of another shape. Stroke-like objects are then compared with the object at the same position in the normal image field and a so-called area ratio of the number of black pixels in the normal image to the number of black pixels in the more intense image is determined. Stroke images having less than a minimum value of area ratio are subjected to a normal image missing pixel count and the image is deemed acceptable or unacceptable if a predetermined number of pixels are missing in the normal image. The method may be applied selectively to high rate document image capture and recording systems for verification of image quality and the health of the recording system.

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Oakland, CA, United States of America

Cynthia D Ott