Abstract: A fiducial on a backer of a flatbed scanner is used for determining a media size of a target scanned on the platen of the scanner. The fiducial is comprised of a plurality of symbols, either arranged in a predetermined pattern or randomly within a fiducial frame, and is placed at a predetermined location on the backer on the scanner lid. Each symbol has a finish that reflects light differently than a finish on the backer and has a high peak correlation value and a low off-peak correlation value when scanned. Image data from a scan of a target along with the backer is searched for the fiducial image. When the fiducial image is found, the media is selected to be of a first shorter length target type and, when the fiducial is not found, the target is selected to be of a second longer length target type.

Abstract: A fiducial on a backer of a flatbed scanner is used for determining a media size of a target scanned on the platen of the scanner. The fiducial is comprised of a plurality of symbols, either arranged in a predetermined pattern or randomly within a fiducial frame, and is placed at a predetermined location on the backer on the scanner lid. Each symbol has a finish that reflects light differently than a finish on the backer and has a high peak correlation value and a low off-peak correlation value when scanned. Image data from a scan of a target along with the backer is searched for the fiducial image. When the fiducial image is found, the media is selected to be of a first shorter length target type and, when the fiducial is not found, the target is selected to be of a second longer length target type.

Abstract: A method for determining a media size of a target scanned on the platen of the flatbed scanner using a fiducial placed on a backer of the flatbed scanner at a predetermined location. The fiducial is comprised of a plurality of objects, either placed in a predetermined pattern or randomly within a fiducial frame. A target is placed on the platen of the flatbed scanner and scanned along with the backer. The scanned image data of the target and backer is searched for the fiducial image. When the fiducial image is found, the media is selected to be of a first target type of a first media size, and, when the fiducial is not found the target is selected to be of a second target type of a second media size greater than the first media size.

Abstract: A method for determining a media size of a target scanned on the platen of the flatbed scanner using a fiducial placed on a backer of the flatbed scanner at a predetermined location. The fiducial is comprised of a plurality of objects, either placed in a predetermined pattern or randomly within a fiducial frame. A target is placed on the platen of the flatbed scanner and scanned along with the backer. The scanned image data of the target and backer is searched for the fiducial image. When the fiducial image is found, the media is selected to be of a first target type having a first length, and, when the fiducial is not found the target is selected to be of a second target type have a second length longer than the first length.

Abstract: Systems and methods convert to binary an input image having pixels defining text and background. Thresholds are determined by which pixels in the input image and a corresponding blurred image will be defined as either binary black or binary white. Thresholds derive from grouped together neighboring pixels having pixels separated out that correspond to the background. For pixels of the input image defined as binary black and having corresponding pixels in the blurred image defined as binary black relative to their thresholds, those are set to black in the binary image, else they are set white. Techniques for devising thresholds, blurring images, grouping together pixels, statistical analysis, etc., typify the embodiments.

Abstract: Systems and methods convert to binary an input image having pixels defining text and background. Thresholds are determined by which pixels in the input image and a corresponding blurred image will be defined as either binary black or binary white. Thresholds derive from grouped together neighboring pixels having pixels separated out that correspond to the background. For pixels of the input image defined as binary black and having corresponding pixels in the blurred image defined as binary black relative to their thresholds, those are set to black in the binary image, else they are set white. Techniques for devising thresholds, blurring images, grouping together pixels, statistical analysis, etc., typify the embodiments.

Abstract: Systems and methods convert to binary an input image having pixels defining text and background. Thresholds are determined by which pixels in the input image and a corresponding blurred image will be defined as either binary black or binary white. Thresholds derive from grouped together neighboring pixels having pixels separated out that correspond to the background. For pixels of the input image defined as binary black and having corresponding pixels in the blurred image defined as binary black relative to their thresholds, those are set to black in the binary image, else they are set white. Techniques for devising thresholds, blurring images, grouping together pixels, statistical analysis, etc., typify the embodiments.

Abstract: Systems and methods convert to binary an input image having pixels defining text and background. Thresholds are determined by which pixels in the input image and a corresponding blurred image will be defined as either binary black or binary white. Thresholds derive from grouped together neighboring pixels having pixels separated out that correspond to the background. For pixels of the input image defined as binary black and having corresponding pixels in the blurred image defined as binary black relative to their thresholds, those are set to black in the binary image, else they are set white. Techniques for devising thresholds, blurring images, grouping together pixels, statistical analysis, etc., typify the embodiments.

Abstract: Systems and methods convert to binary an input image having pixels defining text and background. Thresholds are determined by which pixels in the input image and a corresponding blurred image will be defined as either binary black or binary white. Thresholds derive from grouped together neighboring pixels having pixels separated out that correspond to the background. For pixels of the input image defined as binary black and having corresponding pixels in the blurred image defined as binary black relative to their thresholds, those are set to black in the binary image, else they are set white. Techniques for devising thresholds, blurring images, grouping together pixels, statistical analysis, etc., typify the embodiments.