Abstract: A scanning system and method for locating a point within a region. The method may: 1) determine or locate a region of interest in the region; 2) determine one or more characteristics of the region of interest within the region, wherein the region of interest includes the point of interest; 3) determine a continuous trajectory based on the one or more characteristics of the region of interest; 4) measure the region of interest at a plurality of points along the continuous trajectory to generate a sample data set; 5) perform a surface fit of the sample data set using the approximate model to generate a parameterized surface; and 6) calculate a location of the point of interest based on the parameterized surface. The method may include measuring the region at and/or near the calculated location to confirm the solution, and may also include generating output comprising the results.

Abstract: A scanning system and method for scanning for an object within a region, or for locating a point within a region. Embodiments of the invention include a method for scanning for an object within a region using a Low Discrepancy Curve (LDC) scanning scheme. The method may: 1) generate a Low Discrepancy Sequence (LDS) of points in the region; 2) calculate an LDC in the region based on the LDS of points; and 3) scan the region along the LDC to determine one or more characteristics of the object in response to the scan. In calculating the LDC in the region based on the LDS of points, the method may connect sequential pairs of the LDS with contiguous orthogonal line segments (each parallel to a respective axis of the region), then sample the segments, generating points which may be used to generate the LDC, such as by a curve fit.

Abstract: A system and method for generating a curve in a region, e.g., a Low Discrepancy Curve. The method may generate an unbounded Low Discrepancy Point (LDP); apply one or more boundary conditions to the unbounded LDP to generate a bounded LDP located within the region; repeat said generating and said applying one or more boundary conditions one or more times, generating a Low Discrepancy Sequence (LDS) in the region; store the LDS; and generate output comprising the LDS, wherein the LDS defines the curve in the region. The method may scan the region according to the defined curve. In generating the unbounded LDP, the method may select two or more irrational numbers, a step size epsilon (&egr;), and a starting position; initialize a current position to the starting position; and increment components of the current position based on &egr; and the irrational numbers to generate the unbounded LDP.

Abstract: A system and method for generating a curve, such as a Low Discrepancy Curve, on a surface, such as an abstract surface with a Riemannian metric. The system may comprise a computer which includes a CPU and a memory medium which is operable to store one or more programs executable by the CPU to perform the method. The method may: 1) parameterize the surface; 2) select a curve, such as a Low Discrepancy Curve, in a parameter space, for example, a simple space such as a unit square; 3) re-parameterize the surface, for example, re-parameterize the surface such that a ratio of line and area elements of the surface based on a Riemannian metric is constant; and 4) map the curve onto the surface using the re-parameterization. The method may also generate output comprising information regarding the mapped curve, for example, displaying the mapped curve on a display device.

Abstract: A system and method for programmatically generating a second graphical program based on a first graphical program. The first graphical program may be associated with a first programming development environment. For example, a user may have interactively created the first graphical program from within the first programming development environment, e.g., by using an editor to place various nodes on a block diagram, such that the nodes visually indicate functionality of the first graphical program. The method may operate to automatically, i.e., programmatically, generate a second graphical program based on the first graphical program, such that the second graphical program is associated with a second programming development environment. The method may generate the second graphical program programmatically, without relying on user input, or may prompt for user input to determine various options to use in generating the second graphical program.

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.

Abstract: A system and method for programmatically generating and modifying graphical programs, in response to receiving program information. The program information may specify functionality of the graphical program or graphical program portion. During execution of a graphical program generation (GPG) program, the GPG program may be operable to receive the program information. In response to the program information, the GPG program may programmatically generate a graphical program (or graphical program portion) that implements the specified functionality. Thus, the GPG program may generate different graphical programs, depending on the program information received. The GPG program may have any of various purposes or applications. In some embodiments, the GPG program may be a program or application which a user utilizes to construct or characterize a computational process.

Abstract: A system and method for programmatically generating a graphical program or a portion of a graphical program, in response to receiving program information. The program information may specify functionality of the graphical program or graphical program portion to be generated. During execution of a graphical program generation (GPG) program, the GPG program may be operable to receive the program information. In response to the program information, the GPG program may programmatically generate a graphical program (or graphical program portion) that implements the specified functionality. Thus, the GPG program may generate different graphical programs, depending on the program information received. The GPG program may have any of various purposes or applications. In some embodiments, the GPG program may be a program or application which a user utilizes to construct or characterize a computational process.

Abstract: A system and method for performing pattern matching to locate zero or more instances of a template image in a target image. The method first comprises sampling the template image using a Low Discrepancy sequence, also referred to as a quasi-random sequence, to determine a plurality of sample pixels in the template image which accurately characterize the template image. The Low Discrepancy sequence is designed to produce sample points which maximally avoid each other. After the template image is sampled or characterized, the method then performs pattern matching using the sample pixels and the target image to determine zero or more locations of the template image in the target image. The method may also perform a local stability analysis around at least a subset of the sample pixels to determine a lesser third number of sample pixels which have a desired degree of stability, and then perform pattern matching using the third plurality of sample pixels.

Abstract: A system and method for performing pattern matching to locate zero or more instances of a template image in a target image. The method first comprises sampling the template image using a Low Discrepancy sequence, also referred to as a quasi-random sequence, to determine a plurality of sample pixels in the template image which accurately characterize the template image. The Low Discrepancy sequence is designed to produce sample points which maximally avoid each other. After the template image is sampled or characterized, the method then performs pattern matching using the sample pixels and the target image to determine zero or more locations of the template image in the target image. The method may also perform a local stability analysis around at least a subset of the sample pixels to determine a lesser third number of sample pixels which have a desired degree of stability, and then perform pattern matching using the third plurality of sample pixels.

Abstract: A system and method for performing pattern matching to locate zero or more instances of a template image in a target image. The method first comprises sampling the template image using a Low Discrepancy sequence, also referred to as a quasi-random sequence, to determine a plurality of sample pixels in the template image which accurately characterize the template image. The Low Discrepancy sequence is designed to produce sample points which maximally avoid each other. After the template image is sampled or characterized, the method then performs pattern matching using the sample pixels and the target image to determine zero or more locations of the template image in the target image. The method may also perform a local stability analysis around at least a subset of the sample pixels to determine a lesser third number of sample pixels which have a desired degree of stability, and then perform pattern matching using the third plurality of sample pixels.

Abstract: A device for dewatering suspensions such as sludge or similar dewaterable goods contains several rollers and filtering webs that follow a sinuous path around the rollers. The width of at least one pressure gap, as well as the force which is applied on the goods to be filtered in this pressure gap, may be adjusted by sliding or swivelling so that the ratio between linear pressure and surface pressure can be adapted to the properties of the goods to be dewatered. By influencing this ratio it is possible from a standard model to cover a wide range of applications by simple and economic means, so that the cost-effectiveness ratio is improved.

Abstract: A conveyor-type sludge filtering device for extracting the liquid component from the sludge, the device including a horizontally moving supported strand of a perforate endless conveyor belt onto which a continuous flow of sludge is deposited, while rows of flow breaker members extend downwardly into the moving sludge, thereby preventing the formation of sludge layers, especially of a belt-plugging bottom layer of solid matter. The flow breakers are preferably wedge-shaped and pivotably supported on transverse rods.