Abstract: A method for identifying an object within a container is provided. The method includes acquiring image data representing an image, applying a morphological operator to the acquired image data to generate morphed image data, calculating a histogram based on the morphed image data, and classifying the image using the calculated histogram. A classification of the image may be displayed and/or stored in a computer-readable memory.

Abstract: A method and system for selective resolution improvement in computed tomography (CT) scanning. The method includes receiving scan data representative of a scanned object from a CT scanner and reconstructing the scan data using a first algorithm to create a first set of reconstructed data. A region of interest is identified within the first set of reconstructed data. A portion of the scan data corresponding to the region of interest is reconstructed using a second algorithm to create a second set of reconstructed data. The first set of reconstructed data and the second set of reconstructed data are combined to create combined reconstructed data.

Abstract: A system and method for identifying an object based on its estimated mass. In one aspect, a method for estimating a mass of an object is provided. The method includes acquiring image data including a plurality of image elements, calculating a histogram based on the image data, calculating a computed tomography (CT) number of the object using an anisotropic erosion operator, and determining a perimeter of the object. The method also includes calculating an estimated mass of the object using the CT number and a first subset of image elements of the plurality of image elements, the first subset of image elements defined by the perimeter of the object, and outputting at least one of the estimated mass of the object and an image including the object.

Abstract: A method and system for selective resolution improvement in computed tomography (CT) scanning. The method includes receiving scan data representative of a scanned object from a CT scanner and reconstructing the scan data using a first algorithm to create a first set of reconstructed data. A region of interest is identified within the first set of reconstructed data. A portion of the scan data corresponding to the region of interest is reconstructed using a second algorithm to create a second set of reconstructed data. The first set of reconstructed data and the second set of reconstructed data are combined to create combined reconstructed data.

Abstract: A method for identifying an object is provided. The method includes acquiring image data, and separating a sheet object from a bulk object within the acquired image data by using a top hat algorithm. Information relating to at least one of the sheet object and the bulk object is outputted.

Abstract: Systems and methods for classifying targets within a container are provided. In one aspect, a method for resolving an alarm raised by an imaging system that includes a component for detecting contraband objects in a container is provided. The method includes receiving a plurality of images from the imaging system, calculating at least one feature for at least one object that caused the alarm, inputting the at least one feature into at least one classifier, rendering a decision about the at least one object based on a vote of the at least one classifier, and rendering a final decision about the container.

Abstract: A system and method for identifying an object based on its estimated mass. In one aspect, a method for estimating a mass of an object is provided. The method includes acquiring image data including a plurality of image elements, calculating a histogram based on the image data, calculating a computed tomography (CT) number of the object using an anisotropic erosion operator, and determining a perimeter of the object. The method also includes calculating an estimated mass of the object using the CT number and a first subset of image elements of the plurality of image elements, the first subset of image elements defined by the perimeter of the object, and outputting at least one of the estimated mass of the object and an image including the object.

Abstract: A method for identifying an object within a container is provided. The method includes acquiring image data representing an image, applying a morphological operator to the acquired image data to generate morphed image data, calculating a histogram based on the morphed image data, and classifying the image using the calculated histogram. A classification of the image may be displayed and/or stored in a computer-readable memory.

Abstract: Systems and methods for classifying targets within a container are provided. In one aspect, a method for resolving an alarm raised by an imaging system is provided, the imaging system alarm triggered by an alarm target including a plurality of objects. The method includes receiving a plurality of images from the imaging system, calculating at least one feature value for each object of the plurality of objects, determining whether each object is part of the alarm target, and rendering a decision on the alarm target.

Abstract: A method for improving the visibility of a scanned image is provided. The method includes scanning a container to generate the scanned image, where the scanned image includes a container image including at least an object of interest image. The method also includes segmenting the object of interest image from the scanned image and distinguishing the object of interest image from the container image.

Abstract: A method for quickly identifying object volumetric data and air volumetric data from image data of an object is disclosed. Significantly, embodiments of the method result in significant savings in disk space and a significant reduction in computer processing time as compared to the types of known three-dimensional image processing methods described above. An explosive detection system is also provided that includes computer executable instructions stored in a memory coupled with a computer processor. When executed by the computer processor, the computer executable instructions cause the computer processor to: operate the imaging system to obtain the image data of the object; sample the image data in three dimensions; identify one or more candidate voxels; and identify, from the one or more candidate voxels, one or more starting voxels.

Abstract: A method and system for speech characterization. One embodiment includes a method for speaker verification which includes collecting data from a speaker, wherein the data comprises acoustic data and non-acoustic data. The data is used to generate a template that includes a first set of “template” parameters. The method further includes receiving a real-time identity claim from a claimant, and using acoustic data and non-acoustic data from the identity claim to generate a second set of parameters. The method further includes comparing the first set of parameters to the set of parameters to determine whether the claimant is the speaker. The first set of parameters and the second set of parameters include at least one purely non-acoustic parameter, including a non-acoustic glottal shape parameter derived from averaging multiple glottal cycle waveforms.

Abstract: A method and system for speech characterization. One embodiment includes a method for speaker verification which includes collecting data from a speaker, wherein the data comprises acoustic data and non-acoustic data. The data is used to generate a template that includes a first set of “template” parameters. The method further includes receiving a real-time identity claim from a claimant, and using acoustic data and non-acoustic data from the identity claim to generate a second set of parameters. The method further includes comparing the first set of parameters to the set of parameters to determine whether the claimant is the speaker. The first set of parameters and the second set of parameters include at least one purely non-acoustic parameter, including a non-acoustic glottal shape parameter derived from averaging multiple glottal cycle waveforms.