Abstract:
A method of determining whether a biometric object is part of a live individual is described. In one such method, image information is acquired from the biometric object by using a sensor, such as an ultrasonic sensor. The image information may be analyzed in at least two analysis stages. One of the analysis stages may be a temporal analysis stage that analyzes changes in the image information obtained during a time period throughout which the biometric object was continuously available to the sensor. For example, a dead/alive stage may analyze differences between image information taken at two different times in order to identify changes from one time to the next. Other stages may focus on aspects of a particular image information set, rather than seeking to assess changes over time. These other stages seek to determine whether an image information set exhibits characteristics similar to those of a live biometric object.
Abstract:
Mobile communication devices, having multiple speakers and/or microphones to perform a number of audio functions, for use with mobile devices, are provided. The microphones may be housed within the communication device housing. To compensate for the unwanted signal feedback between the speakers and microphones, acoustic echo cancellation may be implemented to determine the proper distance and relative location between the speakers and microphones. Acoustic echo cancellation removes the echo from voice communications to improve the quality of the sound. The removal of the unwanted signals captured by the microphones may be accomplished by characterizing the audio signal paths from the speakers to the microphones (speaker-to-microphone path distance profile), including the distance and relative location between the speakers and microphones. The optimal distance and relative location between the speakers and microphones is provided to the user to optimize performance.
Abstract:
Some methods may involve receiving fingerprint image data and a first set of background image data from a fingerprint sensor and determining first processed fingerprint image data via a subtraction of the first set of background image data from the fingerprint image data. Some methods may involve obtaining force data corresponding to a force applied to the fingerprint sensor when the fingerprint image data were obtained. Some methods may involve obtaining a second set of background image data corresponding to the force data. Some methods may involve determining second processed fingerprint image data based, at least in part, on the first processed fingerprint image data and the second set of background image data, and outputting the second processed fingerprint image data. In some examples, determining the second processed fingerprint image data may involve a machine learning model. Some examples may involve estimating residual noise based on the force data.
Abstract:
Systems and methods for multi-spectral ultrasonic imaging are disclosed. In one embodiment, a finger is scanned at a plurality of ultrasonic scan frequencies. Each scan frequency provides an image information set describing a plurality of pixels of the finger including a signal-strength indicating an amount of energy reflected from a surface of a platen on which a finger is provided. For each of the pixels, the pixel output value corresponding to each of the scan frequencies is combined to produce a combined pixel out put value for each pixel. Systems and methods for improving the data capture of multi-spectral ultrasonic imaging are also disclosed.
Abstract:
An adaptive active noise cancellation apparatus performs a filtering operation in a first digital domain and performs adaptation of the filtering operation in a second digital domain.
Abstract:
A liveness-detection method and/or system is disclosed. A method of detecting liveness can comprise obtaining a single ultrasonic image of a biometric object. The single ultrasonic image can be subdivided into a plurality of overlapping sample blocks. Feature vectors can be extracted in a spatial domain and a frequency domain from each of the plurality of sample blocks. The feature vectors can be compared from each of the plurality of sample blocks to a classification model.
Abstract:
An adaptive active noise cancellation apparatus performs a filtering operation in a first digital domain and performs adaptation of the filtering operation in a second digital domain.
Abstract:
Some methods may involve determining whether an object is positioned on or near a portion of a fingerprint sensor system. If an object is positioned on or near the portion of the fingerprint sensor system, an acoustic impedance of at least a portion of the object may be determined. Based at least in part on the acoustic impedance, it may be determined whether the object is a finger.
Abstract:
A method of determining whether a biometric object is part of a live individual is described. In one such method, image information is acquired from the biometric object by using a sensor, such as an ultrasonic sensor. The image information may be analyzed in at least two analysis stages. One of the analysis stages may be a temporal analysis stage that analyzes changes in the image information obtained during a time period throughout which the biometric object was continuously available to the sensor. For example, a dead/alive stage may analyze differences between image information taken at two different times in order to identify changes from one time to the next. Other stages may focus on aspects of a particular image information set, rather than seeking to assess changes over time. These other stages seek to determine whether an image information set exhibits characteristics similar to those of a live biometric object.
Abstract:
A method of determining whether a biometric object is part of a live individual is described. In one such method, image information is acquired from the biometric object by using a sensor, such as an ultrasonic sensor. The image information may be analyzed in at least two analysis stages. One of the analysis stages may be a temporal analysis stage that analyzes changes in the image information obtained during a time period throughout which the biometric object was continuously available to the sensor. For example, a dead/alive stage may analyze differences between image information taken at two different times in order to identify changes from one time to the next. Other stages may focus on aspects of a particular image information set, rather than seeking to assess changes over time. These other stages seek to determine whether an image information set exhibits characteristics similar to those of a live biometric object.