Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Claim Rejections - 35 USC § 102
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
Claim(s) 1-13 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Museth et al. (US20080074419A1).
Regarding claim 1, Museth teaches A model optimization method for additive manufacturing, the method comprising ([0040] a set of algorithms are described for optimizing the implementation of level set modeling and level set surface operators, [0103] FIG. 1, before an object can be edited in the system of the present invention): acquiring an explicit model of a concept design for additive manufacturing; converting the explicit model to an implicit model ([0012] The system allows for input models such as polygon mesh, NURBS, CSGS models by providing a 3D scan conversion component to convert these models into level set models. In one embodiment, the system also provides for scanned volumes to be converted into level set models) represented by a signed distance field formed by a shortest distance from each voxel in a working space to a boundary point of the concept design ([0069] level set models are volumetric, the constructive solid geometry (CSG) operations of union, difference and intersection may be applied to them. This provides a straightforward approach to implementing copy, cut and paste operations on level set surfaces ( components 20, 22, and 24 of FIG. 1). In the level set framework of the present invention, with a positive-inside/negative-outside sign convention for the distance volumes, these are implemented as min/max operations on the voxel values as summarized in Table 1. Any two closed surfaces represented as signed distance volumes can be used as either the main edited model or the cut/copy primitive, [0072] representation of the intersection curve as a point set to be sufficient for defining a shortest distance d for the region-of-influence function, [0185] The first optimization relies the fact that level set models are represented by a signed distance field); determining an unfeasible geometric feature for current additive manufacturing and a detection threshold corresponding thereto ; subjecting the implicit model to unfeasible geometric feature detection and iterative processing for correction and optimization based on the detection threshold of the determined unfeasible geometric feature, to obtain an optimized implicit model ([0080] FIG. 6, demonstrates the smoothing operator applied to a preliminary 3D scan conversion of the Utah teapot. Unwanted artifacts are removed from the region where the spout meets the body of the teapot by first placing a superellipsoid around the region of interest. The left panel shows that scan conversion left errors near the teapot spout. In the middle panel, a superellipsoid is placed around the errors. The right panel shows that the errors are smoothed away. A smoothing operator constrained to only add material (move outward) is applied and the crevices are removed, [0168] However, this method requires updating every voxel in the volume for each iteration, making the computation time a function of the volume rather than the surface area of the model. Because surface editing only requires a single model (level set), it is unnecessary to calculate solutions over the entire range of iso-values); and converting the optimized implicit model to an optimized explicit model ([0012] The system allows for input models such as polygon mesh, NURBS, CSGS models by providing a 3D scan conversion component to convert these models into level set models. In one embodiment, the system also provides for scanned volumes to be converted into level set models, [0155], [0007] 3D scans can be converted to polygonal and parametric surface meshes, [0014] After the application of the level set editing operators to a model, the result can be volume rendered directly or extracted to a polygon mesh. In one embodiment, the method of extracting and rendering Marching Cubes meshes is used) .
Regarding claim 2, Museth teaches The model optimization method for additive manufacturing as claimed in claim 1, wherein subjecting the implicit model to unfeasible geometric feature detection and iterative processing for correction and optimization based on the detection threshold of the determined unfeasible geometric feature to obtain an optimized implicit model comprises: subjecting the implicit model to unfeasible geometric feature detection based on the detection threshold of the determined unfeasible geometric feature ; upon detecting that no unfeasible geometric feature is present in the implicit model, taking a current implicit model to be an optimized implicit model ([0080] FIG. 6, demonstrates the smoothing operator applied to a preliminary 3D scan conversion of the Utah teapot. Unwanted artifacts are removed from the region where the spout meets the body of the teapot by first placing a superellipsoid around the region of interest. The left panel shows that scan conversion left errors near the teapot spout. In the middle panel, a superellipsoid is placed around the errors. The right panel shows that the errors are smoothed away. A smoothing operator constrained to only add material (move outward) is applied and the crevices are removed, [0168] However, this method requires updating every voxel in the volume for each iteration, making the computation time a function of the volume rather than the surface area of the model. Because surface editing only requires a single model (level set), it is unnecessary to calculate solutions over the entire range of iso-values, [0155] If the incremental change in the model is below threshold, done. Otherwise go to step 3); upon detecting that an unfeasible geometric feature is present in the implicit model, establishing a Hamilton-Jacobi equation for a signed distance field of a region where the unfeasible geometric feature is located in the implicit model ([0137] this PDE can effectively be solved using finite difference (FD) schemes originally developed for Hamilton-Jacobi type PDEs. This effectively corresponds to discretization Eq. (4) on a discrete spatial 3D grid and a temporal 1D grid. The use of such grids raises a number of numerical and computational issues that are important to the accuracy and stability of the implementation) assigning a value to a velocity field in the equation according to the principle of correcting an unfeasible geometric feature, and solving the equation to obtain a new signed distance field; and using the new signed distance field to replace the original signed distance field of the region to obtain a new implicit model (Fig. 12, [0046] the velocity and normal vectors at x on the surface, [0048] The speed function is usually based on a set of geometric measures of the implicit level set surface and data inputs. The challenge when working with level set methods is determining how to combine the building blocks to produce a local motion that creates a desired global or regional behavior of the surface), and returning to perform the operation of subjecting the implicit model to unfeasible geometric feature detection based on the detection threshold of the determined unfeasible geometric feature ([0080] FIG. 6, demonstrates the smoothing operator applied to a preliminary 3D scan conversion of the Utah teapot. Unwanted artifacts are removed from the region where the spout meets the body of the teapot by first placing a superellipsoid around the region of interest. The left panel shows that scan conversion left errors near the teapot spout. In the middle panel, a superellipsoid is placed around the errors. The right panel shows that the errors are smoothed away. A smoothing operator constrained to only add material (move outward) is applied and the crevices are removed, [0155] If the incremental change in the model is below threshold, done. Otherwise go to step 3).
Regarding claim 3, Museth teaches The model optimization method for additive manufacturing as claimed in claim 1, wherein two or more unfeasible geometric features are determined; subjecting the implicit model to unfeasible geometric feature detection and iterative processing for correction and optimization based on the detection threshold of the determined unfeasible geometric feature to obtain an optimized implicit model comprises: determining a detection sequence of the unfeasible geometric features; determining a current unfeasible geometric feature to be detected according to the detection sequence; subjecting the implicit model to detection of the current unfeasible geometric feature based on the detection threshold of the current unfeasible geometric feature ([0080] FIG. 6, demonstrates the smoothing operator applied to a preliminary 3D scan conversion of the Utah teapot. Unwanted artifacts are removed from the region where the spout meets the body of the teapot by first placing a superellipsoid around the region of interest. The left panel shows that scan conversion left errors near the teapot spout. In the middle panel, a superellipsoid is placed around the errors. The right panel shows that the errors are smoothed away. A smoothing operator constrained to only add material (move outward) is applied and the crevices are removed, [0168] However, this method requires updating every voxel in the volume for each iteration, making the computation time a function of the volume rather than the surface area of the model. Because surface editing only requires a single model (level set), it is unnecessary to calculate solutions over the entire range of iso-values, [0155] If the incremental change in the model is below threshold, done. Otherwise go to step 3);
when the current unfeasible geometric feature is present in the implicit model, establishing a Hamilton-Jacobi equation for a signed distance field of each region where the current unfeasible geometric feature is located in the implicit model ([0137] this PDE can effectively be solved using finite difference (FD) schemes originally developed for Hamilton-Jacobi type PDEs. This effectively corresponds to discretization Eq. (4) on a discrete spatial 3D grid and a temporal 1D grid. The use of such grids raises a number of numerical and computational issues that are important to the accuracy and stability of the implementation), and assigning a value to a velocity field in the equation according to the principle of correcting the current unfeasible geometric feature, solving the equation to obtain a new signed distance field, using the new signed distance field to replace the original signed distance field of the region, to obtain a new implicit model ([0046] the velocity and normal vectors at x on the surface, [0048] The speed function is usually based on a set of geometric measures of the implicit level set surface and data inputs. The challenge when working with level set methods is determining how to combine the building blocks to produce a local motion that creates a desired global or regional behavior of the surface, [0014] After the application of the level set editing operators to a model, the result can be volume rendered directly or extracted to a polygon mesh. In one embodiment, the method of extracting and rendering Marching Cubes meshes is used), and returning to perform the operation of subjecting the implicit model to detection of the current unfeasible geometric feature based on the detection threshold of the current unfeasible geometric feature ([0080] FIG. 6, demonstrates the smoothing operator applied to a preliminary 3D scan conversion of the Utah teapot. Unwanted artifacts are removed from the region where the spout meets the body of the teapot by first placing a superellipsoid around the region of interest. The left panel shows that scan conversion left errors near the teapot spout. In the middle panel, a superellipsoid is placed around the errors. The right panel shows that the errors are smoothed away. A smoothing operator constrained to only add material (move outward) is applied and the crevices are removed, [0155] If the incremental change in the model is below threshold, done. Otherwise go to step 3); and when the current unfeasible geometric feature is not present in the implicit model, judging whether there is still an undetected unfeasible geometric feature, and if so, returning to perform the operation of determining a current unfeasible geometric feature to be detected according to the detection sequence; otherwise, taking a current implicit model to be an optimized implicit model ([0080] FIG. 6, demonstrates the smoothing operator applied to a preliminary 3D scan conversion of the Utah teapot. Unwanted artifacts are removed from the region where the spout meets the body of the teapot by first placing a superellipsoid around the region of interest. The left panel shows that scan conversion left errors near the teapot spout. In the middle panel, a superellipsoid is placed around the errors. The right panel shows that the errors are smoothed away. A smoothing operator constrained to only add material (move outward) is applied and the crevices are removed, [0168] However, this method requires updating every voxel in the volume for each iteration, making the computation time a function of the volume rather than the surface area of the model. Because surface editing only requires a single model (level set), it is unnecessary to calculate solutions over the entire range of iso-values, [0155] If the incremental change in the model is below threshold, done. Otherwise go to step 3.
Regarding claim 4, Museth teaches The model optimization method for additive manufacturing as claimed in claim 1, wherein two or more unfeasible geometric features are determined; subjecting the implicit model to unfeasible geometric feature detection and iterative processing for correction and optimization based on the detection threshold of the determined unfeasible geometric feature T to obtain an optimized implicit model comprises ([0080] FIG. 6, demonstrates the smoothing operator applied to a preliminary 3D scan conversion of the Utah teapot. Unwanted artifacts are removed from the region where the spout meets the body of the teapot by first placing a superellipsoid around the region of interest. The left panel shows that scan conversion left errors near the teapot spout. In the middle panel, a superellipsoid is placed around the errors. The right panel shows that the errors are smoothed away. A smoothing operator constrained to only add material (move outward) is applied and the crevices are removed, [0168] However, this method requires updating every voxel in the volume for each iteration, making the computation time a function of the volume rather than the surface area of the model. Because surface editing only requires a single model (level set), it is unnecessary to calculate solutions over the entire range of iso-values, [0155] If the incremental change in the model is below threshold, done. Otherwise go to step 3): determining a weight of each unfeasible geometric feature ([0134] algorithm for computing the single-source shortest paths in a weighted, directed graph. In solving this problem, each vertex is assigned a distance, which is the sum of the edge weights along the minimum-weight path from the source vertex); subjecting the implicit model to detection of each unfeasible geometric feature based on the detection threshold of each said unfeasible geometric feature (0155); when an unfeasible geometric feature is present in the implicit model, establishing a Hamilton-Jacobi equation for a signed distance field of each region where an unfeasible geometric feature is present in the implicit model ([0137] this PDE can effectively be solved using finite difference (FD) schemes originally developed for Hamilton-Jacobi type PDEs. This effectively corresponds to discretization Eq. (4) on a discrete spatial 3D grid and a temporal 1D grid. The use of such grids raises a number of numerical and computational issues that are important to the accuracy and stability of the implementation), and assigning a value to a velocity field in the equation according to the principle of correcting the unfeasible geometric feature, solving the equation to obtain a new signed distance field, using the new signed distance field to replace the original signed distance field of the region, to obtain a new current implicit model ([0046] the velocity and normal vectors at x on the surface, [0048] The speed function is usually based on a set of geometric measures of the implicit level set surface and data inputs. The challenge when working with level set methods is determining how to combine the building blocks to produce a local motion that creates a desired global or regional behavior of the surface), and returning to perform the operation of subjecting the implicit model to detection of each unfeasible geometric feature based on the detection threshold of each said unfeasible geometric feature ([0080] FIG. 6, demonstrates the smoothing operator applied to a preliminary 3D scan conversion of the Utah teapot. Unwanted artifacts are removed from the region where the spout meets the body of the teapot by first placing a superellipsoid around the region of interest. The left panel shows that scan conversion left errors near the teapot spout. In the middle panel, a superellipsoid is placed around the errors. The right panel shows that the errors are smoothed away. A smoothing operator constrained to only add material (move outward) is applied and the crevices are removed, [0155] If the incremental change in the model is below threshold, done. Otherwise go to step 3); wherein, when two or more unfeasible geometric features are present in a region of the implicit model, their respective velocity field assigned values are subjected to weighted summation according to the weights of the two or more unfeasible geometric features, to obtain a velocity field overall assigned value for the region, and the velocity field overall assigned value is used to solve the equation to obtain a new signed distance field; and when no unfeasible geometric feature is present in the implicit model, taking a current implicit model to be an optimized implicit model ([0080] FIG. 6, demonstrates the smoothing operator applied to a preliminary 3D scan conversion of the Utah teapot. Unwanted artifacts are removed from the region where the spout meets the body of the teapot by first placing a superellipsoid around the region of interest. The left panel shows that scan conversion left errors near the teapot spout. In the middle panel, a superellipsoid is placed around the errors. The right panel shows that the errors are smoothed away. A smoothing operator constrained to only add material (move outward) is applied and the crevices are removed, [0168] However, this method requires updating every voxel in the volume for each iteration, making the computation time a function of the volume rather than the surface area of the model. Because surface editing only requires a single model (level set), it is unnecessary to calculate solutions over the entire range of iso-values, [0155] If the incremental change in the model is below threshold, done. Otherwise go to step 3).
Regarding claim 5, Museth teaches The model optimization method for additive manufacturing as claimed in claim 1, wherein the determined unfeasible geometric feature comprises a thin wall or small hole ([0042] the flexible handling of changes in the topology of the deformable surface. This implies that LS surfaces can easily represent complicated surface shapes that can, form holes, split to form multiple objects, or merge with other objects to form a single structure) ; and subjecting the implicit model to unfeasible geometric feature detection based on the detection threshold of the determined unfeasible geometric feature comprises ([0080] FIG. 6, demonstrates the smoothing operator applied to a preliminary 3D scan conversion of the Utah teapot. Unwanted artifacts are removed from the region where the spout meets the body of the teapot by first placing a superellipsoid around the region of interest. The left panel shows that scan conversion left errors near the teapot spout. In the middle panel, a superellipsoid is placed around the errors. The right panel shows that the errors are smoothed away. A smoothing operator constrained to only add material (move outward) is applied and the crevices are removed, [0168] However, this method requires updating every voxel in the volume for each iteration, making the computation time a function of the volume rather than the surface area of the model. Because surface editing only requires a single model (level set), it is unnecessary to calculate solutions over the entire range of iso-values, [0155] If the incremental change in the model is below threshold, done. Otherwise go to step 3): extracting a geometric framework of the implicit model ([0014] After the application of the level set editing operators to a model, the result can be volume rendered directly or extracted to a polygon mesh. In one embodiment, the method of extracting and rendering Marching Cubes meshes is used); subjecting the geometric framework and the implicit model to matrix multiplication and an operation to find an absolute value ([0151] The principle curvatures and principle directions are the eigenvalues and eigenvectors of the shape matrix. For an implicit surface, the shape matrix is the derivative of the normalized gradient (surface normals) projected onto the tangent plane of the surface) , to obtain information of the distance from each point on the geometric framework to a geometric boundary of a corresponding region (Fig. 12, [0155] initialize model volume u0 using one of the distance calculations…); and comparing the distance information obtained with the set detection threshold, and determining whether a thin wall or small hole region is present according to the comparison result ([0089] Morphological openings and closings consist of two fundamental operators, dilations Dω and erosions Eω. Dilation creates an offset surface a distance ω outwards from the original surface, and erosion creates an offset surface a distance ω inwards from the original surface. The morphological opening operator Oω is: an erosion followed by a dilation, i.e. Oω=Dω∘Eω, which removes small pieces or thin appendages. A closing is defined as Cω=Eω∘Dω, and closes small gaps or holes within objects, [0080] FIG. 6, demonstrates the smoothing operator applied to a preliminary 3D scan conversion of the Utah teapot. Unwanted artifacts are removed from the region where the spout meets the body of the teapot by first placing a superellipsoid around the region of interest. The left panel shows that scan conversion left errors near the teapot spout. In the middle panel, a superellipsoid is placed around the errors. The right panel shows that the errors are smoothed away. A smoothing operator constrained to only add material (move outward) is applied and the crevices are removed).
Regarding claim 6, Museth teaches The model optimization method for additive manufacturing as claimed in claim 1, wherein the determined unfeasible geometric feature comprises a sharp corner or edge; subjecting the implicit model to unfeasible geometric feature detection based on the detection threshold of the determined unfeasible geometric feature comprises ([0111] This section describes an algorithm for calculating a distance volume from a 3D closed, orientable polygonal mesh composed of triangular faces, edges, vertices, and normals pointing outwards. The algorithm computes the closest point on and shortest signed distance to the mesh by solving the Eikonal equation, |∇φ|=1, by the method of characteristics. The method of characteristics is implemented efficiently with the aid of computational geometry and polyhedron scan conversion, producing an algorithm with computational complexity that is linear in the number of faces, edges, vertices and voxels, [0080] FIG. 6, demonstrates the smoothing operator applied to a preliminary 3D scan conversion of the Utah teapot. Unwanted artifacts are removed from the region where the spout meets the body of the teapot by first placing a superellipsoid around the region of interest. The left panel shows that scan conversion left errors near the teapot spout. In the middle panel, a superellipsoid is placed around the errors. The right panel shows that the errors are smoothed away. A smoothing operator constrained to only add material (move outward) is applied and the crevices are removed, [0168] However, this method requires updating every voxel in the volume for each iteration, making the computation time a function of the volume rather than the surface area of the model. Because surface editing only requires a single model (level set), it is unnecessary to calculate solutions over the entire range of iso-values, [0155] If the incremental change in the model is below threshold, done. Otherwise go to step 3)) : subjecting a signed distance field of the implicit model to a differentiation operation, to obtain a curvature value of each region ([0073] The blending operator moves the surface in a direction that minimizes a curvature measure, on the level set surface); comparing the curvature value with the corresponding detection threshold and determining whether a sharp corner or edge region is present according to the comparison result ([0111] n algorithm for calculating a distance volume from a 3D closed, orientable polygonal mesh composed of triangular faces, edges, vertices, and normals pointing outwards. The algorithm computes the closest point on and shortest signed distance to the mesh by solving the Eikonal equation, |∇φ|=1, by the method of characteristics. The method of characteristics is implemented efficiently with the aid of computational geometry and polyhedron scan conversion, producing an algorithm with computational complexity that is linear in the number of faces, edges, vertices and voxels) .
Regarding claim 7, Museth teaches A model optimization apparatus for additive manufacturing, the apparatus comprising ([0040] a set of algorithms are described for optimizing the implementation of level set modeling and level set surface operators, [0103] FIG. 1, before an object can be edited in the system of the present invention): at least one memory; and at least one processor ([0197] As with processor 1013, in various computing environments, main memory 1015 and mass storage 1012, can reside wholly on server 1026 or computer 1001, [0200] Computer 1001 can send messages and receive data, including program code, through the network(s), network link 1021, and communication interface 1020. In the Internet example, remote server computer 1026 might transmit a requested code for an application program through Internet 1025, ISP 1024, local network 1022 and communication interface 1020. The received code may be executed by processor 1013 as it is received, and/or stored in mass storage 1012, or other non-volatile storage for later execution ; wherein the at least one memory stores a computer program; the at least one processor is configured to call the computer program stored in the at least one memory to make the apparatus perform corresponding operations, the operations comprising ([0201] A computer program product comprises a medium configured to store or transport computer readable code, or in which computer readable code may be embedded: acquiring an explicit model of a concept design for additive manufacturing, and converting the explicit model to an implicit model ([0012] The system allows for input models such as polygon mesh, NURBS, CSGS models by providing a 3D scan conversion component to convert these models into level set models. In one embodiment, the system also provides for scanned volumes to be converted into level set models); the implicit model being represented by a signed distance field formed by the shortest distance from each voxel in a working space to a boundary point of the concept design ([0069] level set models are volumetric, the constructive solid geometry (CSG) operations of union, difference and intersection may be applied to them. This provides a straightforward approach to implementing copy, cut and paste operations on level set surfaces ( components 20, 22, and 24 of FIG. 1). In the level set framework of the present invention, with a positive-inside/negative-outside sign convention for the distance volumes, these are implemented as min/max operations on the voxel values as summarized in Table 1. Any two closed surfaces represented as signed distance volumes can be used as either the main edited model or the cut/copy primitive, [0072] representation of the intersection curve as a point set to be sufficient for defining a shortest distance d for the region-of-influence function, [0185] The first optimization relies the fact that level set models are represented by a signed distance field); determining an unfeasible geometric feature for current additive manufacturing and a detection threshold corresponding thereto; subjecting the implicit model to unfeasible geometric feature detection and iterative processing for correction and optimization based on the detection threshold of the determined unfeasible geometric feature, to obtain an optimized implicit model ([0080] FIG. 6, demonstrates the smoothing operator applied to a preliminary 3D scan conversion of the Utah teapot. Unwanted artifacts are removed from the region where the spout meets the body of the teapot by first placing a superellipsoid around the region of interest. The left panel shows that scan conversion left errors near the teapot spout. In the middle panel, a superellipsoid is placed around the errors. The right panel shows that the errors are smoothed away. A smoothing operator constrained to only add material (move outward) is applied and the crevices are removed, [0168] However, this method requires updating every voxel in the volume for each iteration, making the computation time a function of the volume rather than the surface area of the model. Because surface editing only requires a single model (level set), it is unnecessary to calculate solutions over the entire range of iso-values); and converting the optimized implicit model to an explicit model, thus obtaining an optimized explicit model ([0012] The system allows for input models such as polygon mesh, NURBS, CSGS models by providing a 3D scan conversion component to convert these models into level set models. In one embodiment, the system also provides for scanned volumes to be converted into level set models, [0155], [0007] 3D scans can be converted to polygonal and parametric surface meshes, [0014] After the application of the level set editing operators to a model, the result can be volume rendered directly or extracted to a polygon mesh. In one embodiment, the method of extracting and rendering Marching Cubes meshes is used).
Regarding claim 8, Museth teaches The model optimization apparatus for additive manufacturing as claimed in claim 7, wherein subjecting the implicit model to unfeasible geometric feature detection and iterative processing for correction and optimization based on the detection threshold of the determined unfeasible geometric feature to obtain an optimized implicit model comprises: subjecting the implicit model to unfeasible geometric feature detection based on the detection threshold of the determined unfeasible geometric feature ([0080] FIG. 6, demonstrates the smoothing operator applied to a preliminary 3D scan conversion of the Utah teapot. Unwanted artifacts are removed from the region where the spout meets the body of the teapot by first placing a superellipsoid around the region of interest. The left panel shows that scan conversion left errors near the teapot spout. In the middle panel, a superellipsoid is placed around the errors. The right panel shows that the errors are smoothed away. A smoothing operator constrained to only add material (move outward) is applied and the crevices are removed, [0168] However, this method requires updating every voxel in the volume for each iteration, making the computation time a function of the volume rather than the surface area of the model. Because surface editing only requires a single model (level set), it is unnecessary to calculate solutions over the entire range of iso-values, [0155] If the incremental change in the model is below threshold, done. Otherwise go to step 3); upon detecting that no unfeasible geometric feature is present in the implicit model, taking a current implicit model to be an optimized implicit model; upon detecting that an unfeasible geometric feature is present in the implicit model, establishing a Hamilton-Jacobi equation for a signed distance field of a region where the unfeasible geometric feature is located in the implicit model ([0137] this PDE can effectively be solved using finite difference (FD) schemes originally developed for Hamilton-Jacobi type PDEs. This effectively corresponds to discretization Eq. (4) on a discrete spatial 3D grid and a temporal 1D grid. The use of such grids raises a number of numerical and computational issues that are important to the accuracy and stability of the implementation); assigning a value to a velocity field in the equation according to the principle of correcting an unfeasible geometric feature, and solving the equation to obtain a new signed distance field; and using the new signed distance field to replace the original signed distance field of the region, to obtain a new implicit model (Fig. 12, [0046] the velocity and normal vectors at x on the surface, [0048] The speed function is usually based on a set of geometric measures of the implicit level set surface and data inputs. The challenge when working with level set methods is determining how to combine the building blocks to produce a local motion that creates a desired global or regional behavior of the surface), and returning to perform the operation of subjecting the implicit model to unfeasible geometric feature detection based on the detection threshold of the determined unfeasible geometric feature ([0080] FIG. 6, demonstrates the smoothing operator applied to a preliminary 3D scan conversion of the Utah teapot. Unwanted artifacts are removed from the region where the spout meets the body of the teapot by first placing a superellipsoid around the region of interest. The left panel shows that scan conversion left errors near the teapot spout. In the middle panel, a superellipsoid is placed around the errors. The right panel shows that the errors are smoothed away. A smoothing operator constrained to only add material (move outward) is applied and the crevices are removed, [0155] If the incremental change in the model is below threshold, done. Otherwise go to step 3).
Regarding claim 9, Museth teaches The model optimization apparatus for additive manufacturing as claimed in claim 7, wherein two or more unfeasible geometric features are determined; subjecting the implicit model to unfeasible geometric feature detection and iterative processing for correction and optimization based on the detection threshold of the determined unfeasible geometric feature, to obtain an optimized implicit model, comprises: determining a detection sequence of the unfeasible geometric features; determining a current unfeasible geometric feature to be detected according to the detection sequence; subjecting the implicit model to detection of the current unfeasible geometric feature based on the detection threshold of the current unfeasible geometric feature ([0080] FIG. 6, demonstrates the smoothing operator applied to a preliminary 3D scan conversion of the Utah teapot. Unwanted artifacts are removed from the region where the spout meets the body of the teapot by first placing a superellipsoid around the region of interest. The left panel shows that scan conversion left errors near the teapot spout. In the middle panel, a superellipsoid is placed around the errors. The right panel shows that the errors are smoothed away. A smoothing operator constrained to only add material (move outward) is applied and the crevices are removed, [0168] However, this method requires updating every voxel in the volume for each iteration, making the computation time a function of the volume rather than the surface area of the model. Because surface editing only requires a single model (level set), it is unnecessary to calculate solutions over the entire range of iso-values, [0155] If the incremental change in the model is below threshold, done. Otherwise go to step 3); when the current unfeasible geometric feature is present in the implicit model, establishing a Hamilton-Jacobi equation for a signed distance field of each region where the current unfeasible geometric feature is located in the implicit model ([0137] this PDE can effectively be solved using finite difference (FD) schemes originally developed for Hamilton-Jacobi type PDEs. This effectively corresponds to discretization Eq. (4) on a discrete spatial 3D grid and a temporal 1D grid. The use of such grids raises a number of numerical and computational issues that are important to the accuracy and stability of the implementation), and assigning a value to a velocity field in the equation according to the principle of correcting the current unfeasible geometric feature, solving the equation to obtain a new signed distance field, using the new signed distance field to replace the original signed distance field of the region, to obtain a new implicit model ([0046] the velocity and normal vectors at x on the surface, [0048] The speed function is usually based on a set of geometric measures of the implicit level set surface and data inputs. The challenge when working with level set methods is determining how to combine the building blocks to produce a local motion that creates a desired global or regional behavior of the surface, [0014] After the application of the level set editing operators to a model, the result can be volume rendered directly or extracted to a polygon mesh. In one embodiment, the method of extracting and rendering Marching Cubes meshes is used, and returning to perform the operation of subjecting the implicit model to detection of the current unfeasible geometric feature based on the detection threshold of the current unfeasible geometric feature ([0080] FIG. 6, demonstrates the smoothing operator applied to a preliminary 3D scan conversion of the Utah teapot. Unwanted artifacts are removed from the region where the spout meets the body of the teapot by first placing a superellipsoid around the region of interest. The left panel shows that scan conversion left errors near the teapot spout. In the middle panel, a superellipsoid is placed around the errors. The right panel shows that the errors are smoothed away. A smoothing operator constrained to only add material (move outward) is applied and the crevices are removed, [0155] If the incremental change in the model is below threshold, done. Otherwise go to step 3); and when the current unfeasible geometric feature is not present in the implicit model, judging whether there is still an undetected unfeasible geometric feature, and if so, returning to perform the operation of determining a current unfeasible geometric feature to be detected according to the detection sequence; otherwise, taking a current implicit model to be an optimized implicit model ([0080] FIG. 6, demonstrates the smoothing operator applied to a preliminary 3D scan conversion of the Utah teapot. Unwanted artifacts are removed from the region where the spout meets the body of the teapot by first placing a superellipsoid around the region of interest. The left panel shows that scan conversion left errors near the teapot spout. In the middle panel, a superellipsoid is placed around the errors. The right panel shows that the errors are smoothed away. A smoothing operator constrained to only add material (move outward) is applied and the crevices are removed, [0168] However, this method requires updating every voxel in the volume for each iteration, making the computation time a function of the volume rather than the surface area of the model. Because surface editing only requires a single model (level set), it is unnecessary to calculate solutions over the entire range of iso-values, [0155] If the incremental change in the model is below threshold, done. Otherwise go to step 3.
Regarding claim 10, Museth teaches The model optimization apparatus for additive manufacturing as claimed in claim 7, wherein two or more unfeasible geometric features are determined; subjecting the implicit model to unfeasible geometric feature detection and iterative processing for correction and optimization based on the detection threshold of the determined unfeasible geometric feature, to obtain an optimized implicit model, comprises ([0080] FIG. 6, demonstrates the smoothing operator applied to a preliminary 3D scan conversion of the Utah teapot. Unwanted artifacts are removed from the region where the spout meets the body of the teapot by first placing a superellipsoid around the region of interest. The left panel shows that scan conversion left errors near the teapot spout. In the middle panel, a superellipsoid is placed around the errors. The right panel shows that the errors are smoothed away. A smoothing operator constrained to only add material (move outward) is applied and the crevices are removed, [0168] However, this method requires updating every voxel in the volume for each iteration, making the computation time a function of the volume rather than the surface area of the model. Because surface editing only requires a single model (level set), it is unnecessary to calculate solutions over the entire range of iso-values, [0155] If the incremental change in the model is below threshold, done. Otherwise go to step 3): determining a weight of each unfeasible geometric feature ([0134] algorithm for computing the single-source shortest paths in a weighted, directed graph. In solving this problem, each vertex is assigned a distance, which is the sum of the edge weights along the minimum-weight path from the source vertex); subjecting the implicit model to detection of each unfeasible geometric feature based on the detection threshold of each said unfeasible geometric feature (0155); when an unfeasible geometric feature is present in the implicit model, establishing a Hamilton-Jacobi equation for a signed distance field of each region where an unfeasible geometric feature is present in the implicit model ([0137] this PDE can effectively be solved using finite difference (FD) schemes originally developed for Hamilton-Jacobi type PDEs. This effectively corresponds to discretization Eq. (4) on a discrete spatial 3D grid and a temporal 1D grid. The use of such grids raises a number of numerical and computational issues that are important to the accuracy and stability of the implementation), and assigning a value to a velocity field in the equation according to the principle of correcting the unfeasible geometric feature, solving the equation to obtain a new signed distance field, using the new signed distance field to replace the original signed distance field of the region, to obtain a new current implicit model ([0046] the velocity and normal vectors at x on the surface, [0048] The speed function is usually based on a set of geometric measures of the implicit level set surface and data inputs. The challenge when working with level set methods is determining how to combine the building blocks to produce a local motion that creates a desired global or regional behavior of the surface), and returning to perform the operation of subjecting the implicit model to detection of each unfeasible geometric feature based on the detection threshold of each said unfeasible geometric feature ([0080] FIG. 6, demonstrates the smoothing operator applied to a preliminary 3D scan conversion of the Utah teapot. Unwanted artifacts are removed from the region where the spout meets the body of the teapot by first placing a superellipsoid around the region of interest. The left panel shows that scan conversion left errors near the teapot spout. In the middle panel, a superellipsoid is placed around the errors. The right panel shows that the errors are smoothed away. A smoothing operator constrained to only add material (move outward) is applied and the crevices are removed, [0155] If the incremental change in the model is below threshold, done. Otherwise go to step 3); wherein, when two or more unfeasible geometric features are present in a region of the implicit model, their respective velocity field assigned values are subjected to weighted summation according to the weights of the two or more unfeasible geometric features, to obtain a velocity field overall assigned value for the region, and the velocity field overall assigned value is used to solve the equation to obtain a new signed distance field; and when no unfeasible geometric feature is present in the implicit model, taking a current implicit model to be an optimized implicit model ([0080] FIG. 6, demonstrates the smoothing operator applied to a preliminary 3D scan conversion of the Utah teapot. Unwanted artifacts are removed from the region where the spout meets the body of the teapot by first placing a superellipsoid around the region of interest. The left panel shows that scan conversion left errors near the teapot spout. In the middle panel, a superellipsoid is placed around the errors. The right panel shows that the errors are smoothed away. A smoothing operator constrained to only add material (move outward) is applied and the crevices are removed, [0168] However, this method requires updating every voxel in the volume for each iteration, making the computation time a function of the volume rather than the surface area of the model. Because surface editing only requires a single model (level set), it is unnecessary to calculate solutions over the entire range of iso-values, [0155] If the incremental change in the model is below threshold, done. Otherwise go to step 3).
Regarding claim 11, Museth teaches The model optimization apparatus for additive manufacturing as claimed in claim 7, wherein the determined unfeasible geometric feature comprises a thin wall or small hole ([0042] the flexible handling of changes in the topology of the deformable surface. This implies that LS surfaces can easily represent complicated surface shapes that can, form holes, split to form multiple objects, or merge with other objects to form a single structure); subjecting the implicit model to unfeasible geometric feature detection based on the detection threshold of the determined unfeasible geometric feature comprises ([0080] FIG. 6, demonstrates the smoothing operator applied to a preliminary 3D scan conversion of the Utah teapot. Unwanted artifacts are removed from the region where the spout meets the body of the teapot by first placing a superellipsoid around the region of interest. The left panel shows that scan conversion left errors near the teapot spout. In the middle panel, a superellipsoid is placed around the errors. The right panel shows that the errors are smoothed away. A smoothing operator constrained to only add material (move outward) is applied and the crevices are removed, [0168] However, this method requires updating every voxel in the volume for each iteration, making the computation time a function of the volume rather than the surface area of the model. Because surface editing only requires a single model (level set), it is unnecessary to calculate solutions over the entire range of iso-values, [0155] If the incremental change in the model is below threshold, done. Otherwise go to step 3): extracting a geometric framework of the implicit model; subjecting the geometric framework and the implicit model to matrix multiplication and an operation to find an absolute value ([0151] The principle curvatures and principle directions are the eigenvalues and eigenvectors of the shape matrix. For an implicit surface, the shape matrix is the derivative of the normalized gradient (surface normals) projected onto the tangent plane of the surface), to obtain information of the distance from each point on the geometric framework to a geometric boundary of a corresponding region (Fig. 12, [0155] initialize model volume u0 using one of the distance calculations…); and comparing the distance information obtained with the set detection threshold, and determining whether a thin wall or small hole region is present according to the comparison result ([0089] Morphological openings and closings consist of two fundamental operators, dilations Dω and erosions Eω. Dilation creates an offset surface a distance ω outwards from the original surface, and erosion creates an offset surface a distance ω inwards from the original surface. The morphological opening operator Oω is: an erosion followed by a dilation, i.e. Oω=Dω∘Eω, which removes small pieces or thin appendages. A closing is defined as Cω=Eω∘Dω, and closes small gaps or holes within objects, [0080] FIG. 6, demonstrates the smoothing operator applied to a preliminary 3D scan conversion of the Utah teapot. Unwanted artifacts are removed from the region where the spout meets the body of the teapot by first placing a superellipsoid around the region of interest. The left panel shows that scan conversion left errors near the teapot spout. In the middle panel, a superellipsoid is placed around the errors. The right panel shows that the errors are smoothed away. A smoothing operator constrained to only add material (move outward) is applied and the crevices are removed).
Regarding claim 12, Museth teaches The model optimization apparatus for additive manufacturing as claimed in claim 7, wherein the determined unfeasible geometric feature comprises a sharp corner or edge; subjecting the implicit model to unfeasible geometric feature detection based on the detection threshold of the determined unfeasible geometric feature comprises ([0111] This section describes an algorithm for calculating a distance volume from a 3D closed, orientable polygonal mesh composed of triangular faces, edges, vertices, and normals pointing outwards. The algorithm computes the closest point on and shortest signed distance to the mesh by solving the Eikonal equation, |∇φ|=1, by the method of characteristics. The method of characteristics is implemented efficiently with the aid of computational geometry and polyhedron scan conversion, producing an algorithm with computational complexity that is linear in the number of faces, edges, vertices and voxels, [0080] FIG. 6, demonstrates the smoothing operator applied to a preliminary 3D scan conversion of the Utah teapot. Unwanted artifacts are removed from the region where the spout meets the body of the teapot by first placing a superellipsoid around the region of interest. The left panel shows that scan conversion left errors near the teapot spout. In the middle panel, a superellipsoid is placed around the errors. The right panel shows that the errors are smoothed away. A smoothing operator constrained to only add material (move outward) is applied and the crevices are removed, [0168] However, this method requires updating every voxel in the volume for each iteration, making the computation time a function of the volume rather than the surface area of the model. Because surface editing only requires a single model (level set), it is unnecessary to calculate solutions over the entire range of iso-values, [0155] If the incremental change in the model is below threshold, done. Otherwise go to step 3): subjecting a signed distance field of the implicit model to a differentiation operation, to obtain a curvature value of each region ([0073] The blending operator moves the surface in a direction that minimizes a curvature measure, on the level set surface); and comparing the curvature value with the corresponding detection threshold, and determining whether a sharp corner or edge region is present according to the comparison result ([0111] n algorithm for calculating a distance volume from a 3D closed, orientable polygonal mesh composed of triangular faces, edges, vertices, and normals pointing outwards. The algorithm computes the closest point on and shortest signed distance to the mesh by solving the Eikonal equation, |∇φ|=1, by the method of characteristics. The method of characteristics is implemented efficiently with the aid of computational geometry and polyhedron scan conversion, producing an algorithm with computational complexity that is linear in the number of faces, edges, vertices and voxels) .
Regarding claim 13, Museth teaches A model optimization apparatus for additive manufacturing, the apparatus comprising ([0040] a set of algorithms are described for optimizing the implementation of level set modeling and level set surface operators, [0103] FIG. 1, before an object can be edited in the system of the present invention): an optimization preparation module for acquiring an explicit model of a concept design for additive manufacturing ([0012] The system allows for input models such as polygon mesh, NURBS, CSGS models by providing a 3D scan conversion component to convert these models into level set models. In one embodiment, the system also provides for scanned volumes to be converted into level set models); and determining an unfeasible geometric feature for current additive manufacturing and a detection threshold corresponding thereto; an implicit model reconstruction module, for converting the explicit model to an implicit model represented by a signed distance field formed by the shortest distance from each voxel in a working space to a boundary point of the concept design ([0080] FIG. 6, demonstrates the smoothing operator applied to a preliminary 3D scan conversion of the Utah teapot. Unwanted artifacts are removed from the region where the spout meets the body of the teapot by first placing a superellipsoid around the region of interest. The left panel shows that scan conversion left errors near the teapot spout. In the middle panel, a superellipsoid is placed around the errors. The right panel shows that the errors are smoothed away. A smoothing operator constrained to only add material (move outward) is applied and the crevices are removed, [0168] However, this method requires updating every voxel in the volume for each iteration, making the computation time a function of the volume rather than the surface area of the model. Because surface editing only requires a single model (level set), it is unnecessary to calculate solutions over the entire range of iso-values, [0069] level set models are volumetric, the constructive solid geometry (CSG) operations of union, difference and intersection may be applied to them. This provides a straightforward approach to implementing copy, cut and paste operations on level set surfaces ( components 20, 22, and 24 of FIG. 1). In the level set framework of the present invention, with a positive-inside/negative-outside sign convention for the distance volumes, these are implemented as min/max operations on the voxel values as summarized in Table 1. Any two closed surfaces represented as signed distance volumes can be used as either the main edited model or the cut/copy primitive, [0072] representation of the intersection curve as a point set to be sufficient for defining a shortest distance d for the region-of-influence function, [0185] The first optimization relies the fact that level set models are represented by a signed distance field)); a detection and optimization iteration module for subjecting the implicit model to unfeasible geometric feature detection and iterative processing for correction and optimization based on the detection threshold of the determined unfeasible geometric feature, to obtain an optimized implicit model ([0080] FIG. 6, demonstrates the smoothing operator applied to a preliminary 3D scan conversion of the Utah teapot. Unwanted artifacts are removed from the region where the spout meets the body of the teapot by first placing a superellipsoid around the region of interest. The left panel shows that scan conversion left errors near the teapot spout. In the middle panel, a superellipsoid is placed around the errors. The right panel shows that the errors are smoothed away. A smoothing operator constrained to only add material (move outward) is applied and the crevices are removed, [0168] However, this method requires updating every voxel in the volume for each iteration, making the computation time a function of the volume rather than the surface area of the model. Because surface editing only requires a single model (level set), it is unnecessary to calculate solutions over the entire range of iso-values); and an explicit model reconstruction module for converting the optimized implicit model to an explicit model, thus obtaining an optimized explicit model ([0012] The system allows for input models such as polygon mesh, NURBS, CSGS models by providing a 3D scan conversion component to convert these models into level set models. In one embodiment, the system also provides for scanned volumes to be converted into level set models, [0155], [0007] 3D scans can be converted to polygonal and parametric surface meshes, [0014] After the application of the level set editing operators to a model, the result can be volume rendered directly or extracted to a polygon mesh. In one embodiment, the method of extracting and rendering Marching Cubes meshes is used).
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant’s disclosure.
Ozdas (US20140306959) discloses objects defined by implicit geometry.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to YVONNE T FOLLANSBEE whose telephone number is (571)272-0634. The examiner can normally be reached Monday - Friday 1pm - 9pm.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Robert Fennema can be reached at (571) 272-2748. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/YVONNE TRANG FOLLANSBEE/Examiner, Art Unit 2117
/ROBERT E FENNEMA/Supervisory Patent Examiner, Art Unit 2117