National Instruments Corporation

Satish V Kumar

Dinesh R Nair

Matthew S Fisher

Darren R Schmidt

Lothar Wenzel

Ram Rajagopal

Kevin M Crotty

Jeffrey L Kodosky

Steven W Rogers

Newton G Petersen

Duncan G Hudson, Iii

Aljosa Vrancic

Subramanian Ramamoorthy

Bruce Smyth

A system and method for creating and using type generic graphical programs. The method may include storing a first graphical program on a memory medium. The first graphical program may have been created based on user input. The first graphical program may include a plurality of nodes and interconnections between the nodes, and the plurality of nodes and interconnections between the nodes may be type generic. User input may be received specifying one or more data types of at least one input and/or at least one output of the first graphical program. The data types may be associated with the first graphical program in response to said user input specifying the one or more data types.

Type generic graphical programming

System and method for performing time-bounded execution of a program. A timed program execution process is initiated, and a timeout process is initiated. A timeout condition is configured in the timeout process at a first priority level, and a rollback state determined for the program. Execution of the program is initiated in the timed program execution process at a second priority level below the first priority level. During execution of the program, the timeout process determines if the timeout condition has occurred, and if so, the timeout process restores the execution of the program to the rollback state, and the timed program execution process resumes execution of the program from the rollback state with the timeout condition. The program exits in the timed program execution process in response to the timeout condition, and the timeout event disabled. The timeout process is terminated, and the timed program execution process is terminated.

Time-bounded program execution

A geometric pattern matching method to locate instances of a template image in a target image using a plurality of models with different feature combinations. A learning phase involves learning geometric information about the template image and creating a model for each of a plurality of different respective parent features. Each model comprises a relationship tree from the respective parent feature to one or more other child features, and hence each model may have different feature combinations. In a matching phase, the method may examine a plurality of different models to determine matches in the target image being analyzed. The matching phase may select different models dynamically based on prior matching results.

Geometric pattern matching using dynamic feature combinations

System and method for determining the presence of an object of interest in a target data set. Portions of a target data set may be located that match an object of interest, e.g., in a template data set, with respect to various information, e.g., edge or boundary information. The invention includes improved methods for mapping point sets or curves to new point sets or curves for curve matching. The method determines the presence of an object of interest in a target data set despite of or using various types of topological transformations of the object of interest in the target data set. One or more mapping operators are determined based on template curves and/or example target curves. Pattern matching is performed on one or more target data sets using the mapping operator(s) to generate pattern matching results, and the pattern matching results output.

Pattern matching system utilizing discrete curve matching with a mapping operator

System and method for determining the presence of an object of interest in a target image. Regions of a target image may be located that match an object of interest, e.g., in a template image, with respect to various information, e.g., luminance, color and/or other types of boundary information. The invention includes improved methods for mapping point sequences (e.g., pixel sequences) or curves to new point sets or curves for curve matching. The method determines the presence of an object of interest in a target image despite of or using various types of topological transformations of the object of interest in the target image. One or more mapping operators are determined based on template curves and/or example target curves. Pattern matching is performed on one or more target images using the mapping operator(s) to generate pattern matching results, and the pattern matching results output.

Image pattern matching utilizing discrete curve matching with a mapping operator

System and method for determining a mapping operator for use in a pattern matching application, where the mapping operator enhances differences between respective objects of interest and background objects, e.g., objects not of interest. First and second information is received regarding an object of interest and objects that may appear with the object of interest in an acquired target data set, respectively. The mapping operator is determined using the first information and the second information by determining a template discrete curve characterizing the object of interest, determining one or more target discrete curves characterizing the background objects, and generating a mapping operator that enhances differences between the mapped template discrete curve and the mapped target discrete curves. The operator is stored in a memory and is operable to be used in a pattern matching application to locate instances of the object of interest in acquired target data sets or images.

Generating a curve matching mapping operator by analyzing objects of interest and background information

System and method for determining the presence of an object of interest in a target image. Regions of a target image may be located that match an object of interest, e.g., in a template image, with respect to various information, e.g., luminance, color and/or other types of boundary information. The invention includes improved methods for mapping point sets or curves to new point sets or curves for curve matching. The method determines the presence of an object of interest in a target image despite of or using various types of topological transformations of the object of interest in the target image. A plurality of mapping operators are determined based on template curves and/or example target curves, e.g., background object curves. Pattern matching is performed on one or more target images using the mapping operators to generate pattern matching results, and the pattern matching results output.

Pattern matching utilizing discrete curve matching with multiple mapping operators

System and method for re-sampling discrete curves, thereby efficiently characterizing point sets or curves in a space. The method may also provide improved means for mapping point sets or curves to new point sets or curves for curve matching. A weight vector or function is determined based on a plurality of discrete curves, e.g., from one or more template data sets or images. The weight function enhances differences between weighted discrete curves. A set of orthonormal polynomials is determined based on the computed weight function, where the set of orthonormal polynomials comprises a set of orthogonal eigenfunctions of a Sturm-Liouville differential equation. Values for a plurality of zeros for one of the set of orthonormal polynomials is determined that comprise resampling points for the plurality of discrete curves. Each of the plurality of discrete curves is resampled based on the determined values of the plurality of zeros.

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Austin, TX, United States of America

Satish V Kumar