Abstract: A blood glucose sensing system includes a sensor and a sensor electronics device. The sensor includes a plurality of electrodes. The sensor electronics device includes stabilization circuitry. The stabilization circuitry causes a first voltage to be applied to one of the electrodes for a first timeframe and causes a second voltage to be applied to one of the electrodes for a second timeframe. The stabilization circuitry repeats the application of the first voltage and the second voltage to continue the anodic—cathodic cycle. The sensor electronics device may include a power supply, a regulator, and a voltage application device, where the voltage application device receives a regulated voltage from the regulator, applies a first voltage to an electrode for the first timeframe, and applies a second voltage to an electrode for the second timeframe.

Abstract: An electronic device and method capture multiple images of a scene of real world at a several zoom levels, the scene of real world containing text of one or more sizes. Then the electronic device and method extract from each of the multiple images, one or more text regions, followed by analyzing an attribute that is relevant to OCR in one or more versions of a first text region as extracted from one or more of the multiple images. When an attribute has a value that meets a limit of optical character recognition (OCR) in a version of the first text region, the version of the first text region is provided as input to OCR.

Abstract: Embodiments disclosed pertain to Optical Character Recognition using Multiple Hypothesis Testing based techniques on images occurring in a variety of settings, including images captured by mobile stations. In some embodiments, a set of bifurcation points for a character cluster in an image may be determined. The character cluster may comprise non-uniformly spaced text or closely spaced text. A plurality of hypotheses may be determined for the character cluster, where each hypothesis is based on a subset of the bifurcation points and comprises a set of words generated from the character cluster. A plurality of scores corresponding to the plurality of hypotheses may be determined, where each score corresponds to a hypothesis, and a hypothesis may be selected from among the plurality of hypotheses based on a score associated with the selected hypothesis.

Abstract: Embodiments disclosed pertain to Optical Character Recognition using Multiple Hypothesis Testing based techniques on images occurring in a variety of settings, including images captured by mobile stations. In some embodiments, a set of bifurcation points for a character cluster in an image may be determined. The character cluster may comprise non-uniformly spaced text or closely spaced text. A plurality of hypotheses may be determined for the character cluster, where each hypothesis is based on a subset of the bifurcation points and comprises a set of words generated from the character cluster. A plurality of scores corresponding to the plurality of hypotheses may be determined, where each score corresponds to a hypothesis, and a hypothesis may be selected from among the plurality of hypotheses based on a score associated with the selected hypothesis.

Abstract: An electronic device and method capture multiple images of a scene of real world at a several zoom levels, the scene of real world containing text of one or more sizes. Then the electronic device and method extract from each of the multiple images, one or more text regions, followed by analyzing an attribute that is relevant to OCR in one or more versions of a first text region as extracted from one or more of the multiple images. When an attribute has a value that meets a limit of optical character recognition (OCR) in a version of the first text region, the version of the first text region is provided as input to OCR.