Abstract:
A computer-based apparatus for labeling medications, including: a processor for a computer configured to: calculate a configuration of a first medication package using a first digital image of the first medication package; create, using the configuration, a package template; receive first prescription information including a name of a patient, a name of a medication, a dosage of the medication, an amount of the medication, and a schedule for taking the medication; create a first custom label, using the package template and the first prescription information, the first custom label including a first plurality of data fields including the first prescription information and a configuration for the first custom label; and transmit first data, including the first custom label with the first prescription information entered in the first plurality of data fields, to a printer.
Abstract:
This disclosure provides methods and systems of embedding and extracting information in a printed document. According to one exemplary embodiment, a method is provided wherein information is encoded by one or more partial or complete gaps in a line associated with a form, and the line gaps are patterned to provide N-bit codes.
Abstract:
Methods and systems for detecting an object borderline. A first image with respect to the object can be captured by an image-capturing unit without a flash light and borderlines of the object can be detected. If the detection is successful, the detected borderlines can be outputted. Otherwise, a second image with respect to the object can be captured by the image-capturing unit by applying a flash light and the borderlines can be detected in the image. A geometric transformation between the two images can then be estimated. Finally, the border lines in the first image can be determined by transforming the borderlines detected in the second image. Such an approach effectively detects the appliance borderlines and avoids artifacts caused by applying flash.
Abstract:
A computer-based apparatus for labeling medications, including: a processor for a computer configured to: calculate a configuration of a first medication package using a first digital image of the first medication package; create, using the configuration, a package template; receive first prescription information including a name of a patient, a name of a medication, a dosage of the medication, an amount of the medication, and a schedule for taking the medication; create a first custom label, using the package template and the first prescription information, the first custom label including a first plurality of data fields including the first prescription information and a configuration for the first custom label; and transmit first data, including the first custom label with the first prescription information entered in the first plurality of data fields, to a printer.
Abstract:
To print a certified document, a user may select or a system may receive a selection of a document to be certified. The system identifies a security template to be used based on the document and/or capabilities of the print device on which the document will be printed. The system may display the document with a non-secure overlay of the selected security template, add a unique security element to the document according to the template, and cause the document to be printed at the selected print device with the added security element without permitting the added security element to be fully displayed or printed on any other device.
Abstract:
A method and system for on-street vehicle parking occupancy estimation via curb detection comprises training a computer system to identify a curb, evaluating image data of the region of interest to determine a region wherein a curb is visible in said region of interest, and estimating a parking occupancy of said region of interest according to said region where said curb is visible.
Abstract:
A method and structure for estimating parking occupancy within an area of interest can include the use of at least two image capture devices and a processor (e.g., a computer) which form at least part of a network. A method for estimating the parking occupancy within the area of interest can include the use of vehicle entry and exit data from the area of interest, as well as an estimated transit time for vehicles transiting through the area of interest without parking.
Abstract:
A method and system for on-street vehicle parking occupancy estimation via curb detection comprises training a computer system to identify a curb, evaluating image data of the region of interest to determine a region wherein a curb is visible in said region of interest, and estimating a parking occupancy of said region of interest according to said region where said curb is visible.
Abstract:
Methods, systems, and processor-readable media for pruning a training dictionary for use in detecting anomalous events from surveillance video. Training samples can be received, which correspond to normal events. A dictionary can then be constructed, which includes two or more classes of normal events from the training samples. Sparse codes are then generated for selected training samples with respect to the dictionary derived from the two or more classes of normal events. The size of the dictionary can then be reduced by removing redundant dictionary columns from the dictionary via analysis of the sparse codes. The dictionary is then optimized to yield a low reconstruction error and a high-interclass discriminability.
Abstract:
Methods, systems and processor-readable media for identifying a vehicle for street parking management. An initial identification of one or more vehicles detected parked along a street can be generated based on one or more of a group of factors. The initial identification can be communicated to a user of the vehicle by transmitting an image indicative of the vehicle parked along the street (e.g., via a mobile communications device). An operation can then be implemented for requesting a confirmation or a non-confirmation as to whether the vehicle detected and displayed on the image is associated with the user. Upon confirmation, an operation can be implemented for identifying the at least one vehicle as the initial identification. Upon non-confirmation, an operation can be implemented to query to identify the vehicle associated with the user from among a group of vehicles displayed via the image.