Abstract: Operations in an application may be displayed using a graphical programming representation. A plurality of interconnected icons may be displayed, where each icon corresponds to an operation included in the application. The plurality of interconnected icons may visually indicate a function implemented by operations in the application. Each displayed icon may correspond to a node in a graphical programming development environment.

Abstract: A system and method for enabling a graphical programming development environment to provide suggested graphical programming operations, such as suggested nodes or icons to include in a graphical program. User input specifying one or more nodes to include in the graphical program may be received. The one or more specified nodes may then be included in the graphical program. One or more suggested nodes to include in the graphical program may be then be automatically displayed or otherwise suggested to the user. The one or more suggested nodes may be based on the nodes already included in the graphical program. In various embodiments, the one or more suggested nodes may be displayed or otherwise suggested in various ways.

Abstract: A system and method for specifying a machine vision process utilizing two or more different program creation methodologies. In one embodiment, the different program creation methodologies may include specifying steps or operations for the process using graphical input panels, e.g., in a “wizard-based” manner, and using graphical programming techniques for other portions, such as to specify decision operations. Thus, optimum program creation methodologies may be used for specifying different respective portions of the process.

Abstract: A user may utilize a prototyping environment to create a sequence of motion control, machine vision, and/or data acquisition (DAQ) operations, e.g., without needing to write or construct code in any programming language. For example, the environment may provide a graphical user interface (GUI) enabling the user to develop/prototype the sequence at a high level, by selecting from and configuring a sequence of operations using the GUI. The prototyping environment application may then be operable to automatically, i.e., programmatically, generate graphical program code implementing the sequence. For example, the environment may generate a standalone graphical program operable to perform the sequence of operations.

Abstract: A system and method for specifying a computer-implemented process utilizing two or more different program creation methodologies. In one embodiment, the different program creation methodologies may include specifying steps or operations for the process using graphical input panels, e.g., in a “wizard-based” manner, and using graphical programming techniques for other portions, such as to specify decision operations. Thus, optimum program creation methodologies may be used for specifying different respective portions of the process. At least a portion of the process may be dependent on prior execution results determined by a previous portion of the process. As an example, for a machine vision inspection process, the previous portion of the process may analyze images of a product, and a subsequent portion of the process may depend on the results of the image analysis, e.g., may either accept or reject the product depending on prior execution results of the image analysis portion.

Abstract: System and method for analyzing an image. A received image, comprising an object or objects, is optionally preprocessed. Invariant shape features of the object(s) are extracted using a generalized invariant feature descriptor. The generalized invariant feature descriptor may comprise a generalized invariant feature vector comprising components corresponding to attributes of each object, e.g., related to circularity, elongation, perimeter-ratio-based convexity, area-ratio-based convexity, hole-perimeter-ratio, hole-area-ratio, and/or functions of Hu Moment 1 and/or Hu Moment 2. Non-invariant features, e.g., scale and reflection, may be extracted to form corresponding feature vectors.

Abstract: A system and method for locating regions in a target image that match a template image with respect to color and pattern information. The method may comprise performing a first-pass search using color information obtained in a color characterization analysis of the template image in order to find a plurality of color match candidate locations. For each color match candidate location, a region proximal to the location may then be searched in detail, based on pattern information obtained in a pattern analysis of the template image.

Abstract: A system and method for creating an image processing algorithm and automatically evaluating the performance of the algorithm. A user may develop an image processing algorithm in an image prototyping environment. The image prototyping environment may provide image processing functions for analyzing, processing, or manipulating various types of images. Once the user has developed an image processing algorithm, the user may execute the algorithm. In response to executing the algorithm, the execution time requirements of the algorithm may be determined. This information may be used, for example, in order to determine whether the image processing algorithm is fast enough to evaluate images that are acquired at a particular rate in a real-time application. The information may also help the user identify portions of the algorithm that need to be modified, e.g., because they are bottlenecks in the algorithm.

Abstract: A system and method for automatically (i.e., programmatically) generating a computer program based on program information, wherein the program includes a graphical user interface (GUI) for specifying input values to or viewing output values from the program. In various embodiments, the program information may comprise any type of information specifying functionality for the generated program. In one embodiment, the program information may comprise information specifying a prototype, and the system and method may automatically (i.e., programmatically) generate a computer program from the prototype, wherein the program includes a graphical user interface for specifying input parameter values to or viewing output parameter values from the program. The prototype may comprise a series of functional operations. One or more input and/or output parameters may be associated with each functional operation.

Abstract: System and method for automatically generating a graphical program to perform an image processing algorithm. A user may develop an image processing algorithm in an image prototyping environment. The image prototyping environment enables the user to easily apply various image processing functions to an image and immediately see the results, in order to develop the desired algorithm. As the user applies each image processing function to an image, the function may be recorded as a step in a script. Once the user has developed an algorithm, the user may request the image prototyping environment to automatically generate a program implementing the image processing algorithm. In various embodiments, the prototyping environment may be operable to generate different types of programs, including text-based and graphical programs.

Abstract: Operations in an application may be displayed using a graphical programming representation. A plurality of interconnected icons may be displayed, where each icon corresponds to an operation included in the application. The plurality of interconnected icons may visually indicate a function implemented by operations in the application. Each displayed icon may correspond to a node in a graphical programming development environment.

Abstract: A system and method for performing pattern matching to locate zero or more instances of a template image in a target image. An image is received by a computer from an image source, e.g., a camera. First pattern matching is performed on the image using a first pattern matching technique to determine a plurality of candidate areas. Second pattern matching is performed on each of the candidate areas using a second different pattern matching technique to generate final pattern match results. An output is generated indicating the final pattern match results. The second pattern matching may determine a second plurality of candidate areas which may be analyzed to determine the final pattern match results. The first pattern matching may use a plurality of pattern matching techniques, the results of which may be used to select a best technique from the plurality of techniques to use for the second pattern match.

Abstract: A system and method for enabling a graphical programming development environment to provide suggested graphical programming operations, such as suggested nodes or icons to include in a graphical program. User input specifying one or more nodes to include in the graphical program may be received. The one or more specified nodes may then be included in the graphical program. One or more suggested nodes to include in the graphical program may be then be automatically displayed or otherwise suggested to the user. The one or more suggested nodes may be based on the nodes already included in the graphical program. In various embodiments, the one or more suggested nodes may be displayed or otherwise suggested in various ways.

Abstract: A system and method for specifying a machine vision process utilizing two or more different program creation methodologies. In one embodiment, the different program creation methodologies may include specifying steps or operations for the process using graphical input panels, e.g., in a “wizard-based” manner, and using graphical programming techniques for other portions, such as to specify decision operations. Thus, optimum program creation methodologies may be used for specifying different respective portions of the process.

Abstract: A system and method for specifying a computer-implemented process utilizing two or more different program creation methodologies. In one embodiment, the different program creation methodologies may include specifying steps or operations for the process using graphical input panels, e.g., in a “wizard-based” manner, and using graphical programming techniques for other portions, such as to specify decision operations. Thus, optimum program creation methodologies may be used for specifying different respective portions of the process. At least a portion of the process may be dependent on prior execution results determined by a previous portion of the process. As an example, for a machine vision inspection process, the previous portion of the process may analyze images of a product, and a subsequent portion of the process may depend on the results of the image analysis, e.g., may either accept or reject the product depending on prior execution results of the image analysis portion.

Abstract: A system and method for developing a sequence of motion control operations. Various embodiments of a motion control prototyping environment application are described. The motion control prototyping environment may be designed to enable a user to easily and efficiently develop/prototype a motion control sequence without requiring the user to perform programming, e.g., without needing to write or construct code in any programming language. For example, the environment may provide a graphical user interface (GUI) enabling the user to develop/prototype the motion control sequence at a high level, by selecting from and configuring a sequence of motion control operations using the GUI.

Abstract: A system and method for configuring a hardware device to execute a prototype. The hardware device may include a programmable hardware element and/or a processor and memory. The prototype may comprise a software entity operable to perform a plurality of executable operations, wherein the prototype is created by a user without requiring user programming. For example, a prototyping environment may provide a library of operations that are specific to a particular problem domain and may enable the user to select various operations from the library for inclusion in the prototype. The prototyping environment may include a graphical user interface that is streamlined for interactively experimenting with various parameters or properties associated with the selected operations and seeing the effects of adjusting the parameters.

Abstract: A user may utilize a prototyping environment to create a sequence of motion control, machine vision, and/or data acquisition (DAQ) operations, e.g., without needing to write or construct code in any programming language. For example, the environment may provide a graphical user interface (GUI) enabling the user to develop/prototype the sequence at a high level, by selecting from and configuring a sequence of operations using the GUI. The prototyping environment application may then be operable to automatically, i.e., programmatically, generate graphical program code implementing the sequence. For example, the environment may generate a standalone graphical program operable to perform the sequence of operations.

Abstract: A system and method for developing a prototype that comprises a sequence of motion control, machine vision, and/or data acquisition (DAQ) “MC/MV/DAQ” operations. A MC/MV/DAQ prototyping environment may be designed to enable a user to easily and efficiently develop/prototype a MC/MV/DAQ sequence (i.e., a sequence of operations which includes one or more motion control, machine vision, and/or DAQ operations) without requiring the user to perform programming, e.g., without needing to write or construct code in any programming language. For example, the environment may provide a graphical user interface (GUI) enabling the user to develop/prototype the MC/MV/DAQ sequence at a high level, by selecting from and configuring a sequence of MC/MV/DAQ operations using the GUI.

Abstract: A system and method for improved image characterization, object placement, and mesh design utilizing Low Discrepancy sequences. The Low Discrepancy sequence is designed to produce sample points which maximally avoid one another, i.e., the distance between any two sample points is maximized. The invention may be applied specifically to methods of image characterization, pattern matching, acquiring image statistics, object location, image reconstruction, motion estimation, object placement, sensor placement, and mesh design, among others. Image characterization is performed by receiving an image and then sampling the image using a Low Discrepancy sequence, also referred to as a quasi-random sequence, to determine a plurality of sample pixels in the image which characterize the image. Sensor placement is performed by generating a Low Discrepancy sequence for the desired placement application, and then selecting locations for the optimal placement of sensors using the generated Low Discrepancy sequence.