Abstract: A process for contextual analysis of radiographic image data can be embodied as a method, system, and computer software program, among other things. The process can include receiving a radiographic image and performing a region analysis including identifying a region within the radiographic images having an estimated atomic number within a predetermined range and determining if the region is in an expected location. The process can also include performing a material feature analysis to identify whether a feature present in the radiographic image is associated with an obscuration characteristic. The process can include providing context information and generating, as output, a region of interest in the radiographic image, the region of interest being determined based upon a set of rules and the region analysis, the material feature analysis, and the context information.

Abstract: A method of determining an effective atomic number, Zeff, of an object may include obtaining a plurality of radiographic images of the object. Each radiographic image can be obtained using a different independent X-ray energy level. An intensity value for each pixel in a region of interest in each radiographic image can be determined. A plurality of measured ratios, R, can be formed using attenuation coefficients from a pair of different radiographic images. At least one adjusted measured ratio, Rm, can be calculated based on the plurality of measured ratios, R, and at least one corresponding estimation coefficient, ?. Zeff values can be assigned based on a comparison of the at least one adjusted measured ratio, Rm to a material attenuation database.

Abstract: A method of arbitrating outputs from a set of threat analysis algorithms or systems. The method can include receiving threat outputs from different threat analysis algorithms. Each threat output can be assigned to a class membership. Rules can be applied based on the threat outputs and the respective class membership. Each rule can provide an amount of support mass to a hypothesis and an amount of uncertainty mass. The rules can have an associated priority value for weighting the masses. A combined belief value for each hypothesis and a total uncertainty value can be determined based on the provided masses. The method can further include generating a decision matrix of the hypotheses and combined belief values. A hypothesis can be selected from the decision matrix based on the combined belief value.

Abstract: A process for contextual analysis of radiographic image data can be embodied as a method, system, and computer software program, among other things. The process can include receiving a radiographic image and performing a region analysis including identifying a region within the radiographic images having an estimated atomic number within a predetermined range and determining if the region is in an expected location. The process can also include performing a material feature analysis to identify whether a feature present in the radiographic image is associated with an obscuration characteristic. The process can include providing context information and generating, as output, a region of interest in the radiographic image, the region of interest being determined based upon a set of rules and the region analysis, the material feature analysis, and the context information.

Abstract: A method for automatically detecting nuclear material using radiographic images of a cargo container includes receiving a plurality of radiographic images of the cargo container and aligning the plurality of images with respect to each other to produce registered images. The method also includes segmenting the registered images using the atomic number and other edge/texture information in order to locate one or more regions of interest within the registered images and estimating atomic number information for each of a predetermined number of portions of the registered images. The method includes assigning a threat level and a confidence value to regions of interest identified as a potential threat and evaluating the regions of interest identified as potential threats using material context information and adjusting, based on the evaluation, the threat level values and confidences of the regions of interest identified as potential threats.

Abstract: A system for segmenting radiographic images of a cargo container can include an object segmentation recognition module adapted to perform a series of functions. The functions can include receiving a plurality of radiographic images of a cargo container, each image generated using a different energy level and segmenting each of the radiographic images using one or more segmentation modules to generate segmentation data representing one or more image segments. The functions can also include identifying image layers within the radiographic images using a plurality of layer analysis modules by providing the plurality of radiographic images and the segmentation data as input to the layer analysis modules, and determining adjusted atomic number values for an atomic number image based on the image layers.

Abstract: A system for segmenting radiographic images of a cargo container can include an object segmentation recognition module adapted to perform a series of functions. The functions can include receiving a plurality of radiographic images of a cargo container, each image generated using a different energy level and segmenting each of the radiographic images using one or more segmentation modules to generate segmentation data representing one or more image segments. The functions can also include identifying image layers within the radiographic images using a plurality of layer analysis modules by providing the plurality of radiographic images and the segmentation data as input to the layer analysis modules, and determining adjusted atomic number values for an atomic number image based on the image layers.

Abstract: A system and method are presented for determining an optimized set of estimation coefficients for use in the gray scale conversion of measured intensity ratios derived from radiographic images of an object. Radiographic images for known materials may be obtained using different source energy levels. Measured training ratios for each known material may be determined intensity values derived from pairs of radiographic images. Standard attenuation data for each known material may also provided. A genetic algorithm may be used to obtain an optimized set of estimation coefficients for the known materials using initial candidate sets of estimation coefficients, the measured training ratios, and the standard attenuation data. The optimized set of estimation coefficients may be used in the gray scale conversion of measured ratios derived from radiographic images of unknown materials for the determination of the atomic number of the unknown materials.

Abstract: Managing and distributing the right to obtain seats from a travel service vendor comprises contracting with the travel service vendor for a total number of seats at a bulk discount rate. A package is defined which includes the right to obtain a prescribed number of seats from the total number of seats in each of several intervals of time. A net present value of the package is computed. An offering amount for the package is defined at the net present value plus a transaction margin. A customer is subscribed to the offering. Any collected offering amounts are invested to generate a ticket payment for a seat claimed by the customer. The travel service vendor is then paid for a seat claimed by the customer using the ticket payment. Customers may also be periodically charged an activity margin. A spread may also be collected from the investment account.

Abstract: A method and computer product is disclosed for arbitrating the outputs of a plurality of recognizers to select a hypothesis associated with a given input from a plurality of hypotheses. Fuzzy membership states are assigned to respective candidate outputs of the plurality of recognizers. At least one rule is selected according to the assigned fuzzy membership states. A selected rule provides a determined amount of support mass for an associated one of the plurality of hypotheses and a determined amount of uncertainty mass. A support value for each hypothesis and an overall uncertainty are determined from the provided mass values. A hypothesis having a highest support value while having an acceptable low level of uncertainty is selected.

Abstract: The present invention is directed to an object recognition system. The system includes a database having stored therein a trained reference vector. The trained reference vector includes a finite string of weighted reference feature elements optimized using a genetic algorithm which uses a dynamic length chromosome. The trained reference vector is optimized relative to a fitness function. The fitness function is an information based function. The trained reference vector corresponds to a known object or class of objects. A sensor is disposed in a surveilled region and configured to generate sensor data. The sensor data corresponds to objects disposed in the surveilled region. A recognition module is coupled to the sensor and the at least one database. The recognition module is configured to generate data object vectors from the sensor data. Each data object vector corresponds to one object.

Abstract: A method and computer product is disclosed for arbitrating the outputs of a plurality of recognizers to select a hypothesis associated with a given input from a plurality of hypotheses. Fuzzy membership states are assigned to respective candidate outputs of the plurality of recognizers. At least one rule is selected according to the assigned fuzzy membership states. A selected rule provides a determined amount of support mass for an associated one of the plurality of hypotheses and a determined amount of uncertainty mass. A support value for each hypothesis and an overall uncertainty are determined from the provided mass values. A hypothesis having a highest support value while having an acceptable low level of uncertainty is selected.

Abstract: Methods for object recognition and systems that implement the methods. In one embodiment, the method of this invention for processing and identifying images includes two steps. In the first step, object profile characteristics are obtained. In the second step, object profile characteristics are utilized to determine object type and orientation. A system that implements the method of this invention is also disclosed.