Lexmark International, Inc.

Stuart Willard Daniel

Steven Frank Weed

Tomasz Jan Cholewo

Michael Ray Timperman

Ahmed Hamad Mohamed Eid

Shaun Timothy Love

Mohamed Nooman Ahmed

Michael E Lhamon

Charles Edward Grieshaber

Amanda Kay Bridges

William James Gardner Flowers

Chad Eugene McQuillen

Stacy Lee Simpson

Dennis Herbert Hasselbring

Chengwu Cui

Brian Wesley Damon

A mobile device with camera automatically captures an image of a check from a video sequence. A computing application assesses quality metrics of a frame of the video and, if acceptable, initiates capture of the check in that frame without user selection. Metrics include an aspect ratio of the check, image quality of the routing transit symbols that delineate a routing transit number on a MICR line of the check, distances between the routing transit symbols and to an edge of the check, recognition of digits of the routing transit number, checksum of the routing transit numbers, and image sharpness. Other embodiments note cropping of the check from the background of the image, properly orienting the check for viewing, and providing color coded visual feedback to users about the quality of the image frame about the check, to name a few.

Automatically capturing and cropping image of check from video sequence for banking or other computing application

A system and methods for selecting a region of pixels in an image displayed on a touch-sensitive interface is disclosed. The method for selecting the region of pixels is based on determined connectivity of pixels in the image indicating content of the image and includes determining connected pixels on the image representing the content without performing character recognition, detecting a text selection gesture indicative of selecting the region in the image, determining coordinates of the text selection gesture performed on the touch-sensitive interface and selecting the region in the image by bounding a first set of pixels located at a proximity from the coordinates of the text selection gesture.

Methods of content-based image area selection

A method for controlling a peripheral device includes receiving input from a user at a workstation adapted to the user, determining whether the received input can be valid, generating a job ticket from the valid input, sending the job ticket to the peripheral device and receiving an identifier representing the job ticket from the peripheral device.

Access to networked peripheral device for impaired users

A method for an impaired user to control a peripheral device including receiving key-value pair input from the user, determining whether the received input is valid and executing a job generated from the valid received key-value pair input.

Peripheral device

Methods and devices for converting printed media into audio data. In one embodiment, a device includes a scanning platform for supporting the document to be scanned, a scanning mechanism for converting images on the document into image data, and a processor configured to convert the scanned image data into audio data. The device may further include printer components configured to create a hardcopy of the image data, an audio device such as a speaker, and an interface for outputting the image data or audio data.

Method and device for converting scanned text to audio data via connection lines and lookup tables

The present invention relates to providing a printing device which allows for user authentication. The printing device may communicate with the authentication device using universal serial bus (USB) protocol, wherein the printing device contains a universal serial bus (USB) host. User authentication may encompass the provision of valid identifying information or presenting sufficient funds as a condition prior to performing a print job or granting access to data.

USB host device for printer interface

Method for shading one of a first plurality of sensing elements of an optical sensor. High-reflectivity and low-reflectivity reference values of the output signal of each of a second plurality of sensing elements of the sensor are obtained. An average or nominal high-reflectivity value of the high-reflectivity reference values for each sensing element of the second plurality is calculated. An average or nominal low-reflectivity value of the low-reflectivity reference values for each sensing element of the second plurality is calculated. An offset value for one of the sensing elements of the first plurality is calculated using at least the average or nominal high-reflectivity values and the average or nominal low-reflectivity values. The one sensing element of the first plurality is calibrated using at least the calculated offset value. In one example, the first plurality and the second plurality are identical.

Shading an optical sensing element such as in a scanner

Method for shading an optical sensing element of an optical sensor. Reference values are sequentially obtained of the output signal of the sensing element while relatively moving the optical sensor including the sensing element over a shading reference target. An edge detection filter is applied to each of the reference values obtained in step a) in determining if each of the reference values is or is not from an optical defect on the shading calibration strip. An average is calculated of the reference values obtained while excluding each of the reference values determined to be from any optical defect in calculating the average. The output signal of the sensing element is calibrated to the shading reference target using at least the calculated average.

Method for shading an optical sensing element such as in a scanner

A method of converting a first set of input color values, such as RGB color values, into a set of device colorants, such as CMY color values, includes the step of providing a look-up table associating a respective, predetermined set of CMY color values with each of a plurality of selected sets of RGB color values. The first set of RGB color values includes a first red color value, a first green color value and a first blue color value. A first random number is added to the first red color value to obtain a randomized red color value. A second random number is added to the first green color value to obtain a randomized green color value. A third random number is added to the first blue color value to obtain a randomized blue color value. Each of the randomized red color value, the randomized green color value and the randomized blue color value are compiled together to obtain a set of randomized RGB color values. A closest one of the selected sets of RGB color values in the look-up table is determined which is closest to the set of randomized RGB color values. The first set of RGB color values is converted into a set of CMY color values that is associated with the closest one of the selected sets of RGB color values in the look-up table. The random numbers which are added to the original RGB values are derived through a deterministic process based on the low order bits of those values.

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Lexington, KY, United States of America

Stuart Willard Daniel