DETAILED ACTION
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 Status
Claims 1-10 are pending for examination in the Application No. 18/211,244 filed June 17th, 2023.
Priority
Acknowledgment is made of applicant’s claim for foreign priority under 35 U.S.C. 119 (a)-(d). The certified copy has been filed as Chinese (CN) Patent Application No. 202310246254.0, filed on March 14th, 2023.
Claim Interpretation
The following is a quotation of 35 U.S.C. 112(f):
(f) Element in Claim for a Combination. – An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The following is a quotation of pre-AIA 35 U.S.C. 112, sixth paragraph:
An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The claims in this application are given their broadest reasonable interpretation using the plain meaning of the claim language in light of the specification as it would be understood by one of ordinary skill in the art. The broadest reasonable interpretation of a claim element (also commonly referred to as a claim limitation) is limited by the description in the specification when 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is invoked.
As explained in MPEP § 2181, subsection I, claim limitations that meet the following three-prong test will be interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph:
(A) the claim limitation uses the term “means” or “step” or a term used as a substitute for “means” that is a generic placeholder (also called a nonce term or a non-structural term having no specific structural meaning) for performing the claimed function;
(B) the term “means” or “step” or the generic placeholder is modified by functional language, typically, but not always linked by the transition word “for” (e.g., “means for”) or another linking word or phrase, such as “configured to” or “so that”; and
(C) the term “means” or “step” or the generic placeholder is not modified by sufficient structure, material, or acts for performing the claimed function.
Use of the word “means” (or “step”) in a claim with functional language creates a rebuttable presumption that the claim limitation is to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites sufficient structure, material, or acts to entirely perform the recited function.
Absence of the word “means” (or “step”) in a claim creates a rebuttable presumption that the claim limitation is not to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is not interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites function without reciting sufficient structure, material or acts to entirely perform the recited function.
Claim limitations in this application that use the word “means” (or “step”) are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action. Conversely, claim limitations in this application that do not use the word “means” (or “step”) are not being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action.
This application includes one or more claim limitations that do not use the word “means,” but are nonetheless being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, because the claim limitation(s) uses a generic placeholder that is coupled with functional language without reciting sufficient structure to perform the recited function and the generic placeholder is not preceded by a structural modifier, as explained in MPEP § 2181, subsection I (note that the list of generic placeholders below is not exhaustive, and other generic placeholders may invoke 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph):
A. The Claim Limitation Uses the Term "Means" or "Step" or a Generic Placeholder (A Term That Is Simply A Substitute for "Means")
With respect to the first prong of this analysis, a claim element that does not include the term "means" or "step" triggers a rebuttable presumption that 35 U.S.C. 112(f) does not apply. When the claim limitation does not use the term "means," examiners should determine whether the presumption that 35 U.S.C. 112(f) does not apply is overcome. The presumption may be overcome if the claim limitation uses a generic placeholder (a term that is simply a substitute for the term "means"). The following is a list of non-structural generic placeholders that may invoke 35 U.S.C. 112(f): "mechanism for," "module for," "device for," "unit for," "component for," "element for," "member for," "apparatus for," "machine for," or "system for." Welker Bearing Co., v. PHD, Inc., 550 F.3d 1090, 1096, 89 USPQ2d 1289, 1293-94 (Fed. Cir. 2008); Mass. Inst. of Tech. v. Abacus Software, 462 F.3d 1344, 1354, 80 USPQ2d 1225, 1228 (Fed. Cir. 2006); Personalized Media, 161 F.3d at 704, 48 USPQ2d at 1886–87; Mas-Hamilton Group v. LaGard, Inc., 156 F.3d 1206, 1214-1215, 48 USPQ2d 1010, 1017 (Fed. Cir. 1998). Note that there is no fixed list of generic placeholders that always result in 35 U.S.C. 112(f) interpretation, and likewise there is no fixed list of words that always avoid 35 U.S.C. 112(f) interpretation. Every case will turn on its own unique set of facts.
Such claim limitation(s) is/are:
"storage device, configured to store instructions;" in claim 6 implemented on hardware disclosed in paras. [0030] (e.g., "a storage device, e.g., a non-transitory computer-readable medium…").
Because this/these claim limitation(s) is/are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, it/they is/are being interpreted to cover the corresponding structure described in the specification as performing the claimed function, and equivalents thereof.
If applicant does not intend to have this/these limitation(s) interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, applicant may: (1) amend the claim limitation(s) to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph (e.g., by reciting sufficient structure to perform the claimed function); or (2) present a sufficient showing that the claim limitation(s) recite(s) sufficient structure to perform the claimed function so as to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph.
Claim Rejections - 35 USC § 103
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 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claims 1-10 are rejected under 35 U.S.C. 103 as being unpatentable over Hartfiel et al. (Hartfiel; US 2020/0388059 A1).
Regarding claim 1, Hartfiel discloses a contour line processing method (para(s). [0003], recite(s)
[0003] “Design files may use vector-based graphics or raster graphics to depict the designed objects. Design files, particularly older files, may be of varying quality. It is desirable for a design file to include polygon attributes, to define the boundary of object(s) depicted in the design file, for easier editing and modification. However, in some cases, a design file may not include polygon attributes defining the boundary of the object(s). Rather, the design file will include lines or line segments that form the object(s) boundaries. To assign polygon attributes to the objects in the design file, the lines/line segments must be connected to define polygons corresponding to the object(s) boundaries…”
, where “line segments that form the object(s) boundaries” are contour lines), comprising
obtaining a computer-aided design (CAD) image file and detecting a plurality of line segments from the CAD image file (para(s). [0049], recite(s)
[0049] “Now referring to FIG. 1A, illustrated therein is a flowchart of method 100 for automatically tracing polygons in a drawing source file. At 102, a source file is accessed. The source file may be one of a plurality of source files stored in a database (202). The source file may be a CAD, SVG, DXF, or other drawing file containing vector line art…”
, where the “CAD” image file (i.e., “design file”) comprises of a plurality of “line segments” as recited in para. [0003] above—see citation in preceding limitation above);
performing a first morphological operation on the plurality of line segments to (para(s). [0056], recite(s)
[0056] “Referring back to FIG. 1A, at 116, morphological dilation, performed by a dilator (220) of the processor (204), is applied to the simplified vector line art (216). Morphological dilation is a known image processing technique to make objects generally more visible and fill in small gaps in objects. For example, thin lines will appear thicker following morphological dilation. Also, gaps between lines, will be filled in following dilation, if a structuring element of sufficient size is used. The morphological dilation is applied with a structuring element in the form of a circle with radius, ε>0. The result of Act 116 is a polygonal approximation (222) of the simplified vector line art (216). At 118, the polygonal approximation (222) is stored in the memory (208).”
, where “dilation” is a first morphological operation)
(para(s). [0056]—see citation in preceding limitation above—, where the “polygonal approximation” is a union block);
performing a second morphological operation on the union block to generate a processed block (para(s). [0058], recite(s)
[0058] “Referring back to FIG. 1A, at 120, a geometric subtractor (224) of the processor (204), subtracts the polygonal approximation (222) from the source file canvas bounds (210). The source file canvas bounds (210) is treated as a single polygon and the polygonal approximation (222) is subtracted from the canvas bounds (210) leaving a set of contracted visual polygons (226) representing closed and nearly closed regions in the image, eroded by epsilon ε. The erosion is a result of subtraction. The subtracted polygon is an epsilon ‘wider’ than the polygon is, in the diagram at the component edges. At 122, the contracted visual polygons (226) are stored in the memory (208).”
, where the “erosion” resulting from the subtraction is a second morphological operation on the union block (e.g., “polygonal approximation”) to generate a processed block (e.g., the “contracted visual polygons”)); and
determining a target contour block according to the processed block (para(s). [0059] and [0064], recite(s)
[0060] “…The true visual polygons (228) represent fully closed regions in the image, eroded by ε. That is, when viewed in the plane, the true visual polygons (228) will appear to be polygonal shapes. At 126, the true visual polygons (228) are stored in the memory (208).”
[0064] “Referring back to FIG. 1A, method 100 is an automated method for implementation by a computer system, thereby removing human error and bias when tracing polygon boundaries from the vector imagery in the source file…”
, where the “true visual polygons” is determining a target contour block (e.g., “polygon boundaries”) according to the processed block (e.g., the “fully closed regions in the image, eroded by ε”)).
Where Hartfiel does not specifically disclose
…generate a plurality of blocks; and
performing a union operation on the plurality of blocks to generate a union block;
Hartfiel teaches in another embodiment in the same field of endeavor of contour line processing
…generate a plurality of blocks (para(s). [0064], recite(s)
[0064] “Referring back to FIG. 1A, method 100 is an automated method for implementation by a computer system, thereby removing human error and bias when tracing polygon boundaries from the vector imagery in the source file. However, the salient inferred polygons (232) returned by method 100 may contain discontinuities in polygon boundaries. Thus, it is desirable to have a method to automatically identify and repair discontinuities in polygons.”
, where “polygons” are a plurality of blocks); and
performing a union operation on the plurality of blocks to generate a union block (para(s). [0073] and [0076], recite(s)
[0073] “At 150, an edge combiner (244) of the processor (204) combines edges within each set of colinear edges to fill in the gaps between colinear edges in that set. The colinear edges within a set are considered in pairs for combining based on the order of appearance on the common line. If the pair of colinear edges are separated by a gap having a minimum distance on the common line, the pair of edges and intervening gap are removed from the polygon boundary and replaced by a single spanning segment on the common line. Act 150 is performed for each set of colinear edges within a polygon boundary. If all gaps in the polygon boundary are filled at Act 150, the method 140 proceeds to Act 154. If gaps remain, the method 140 proceeds to Act 152.”
[0076] “Referring to FIG. 3I, illustrated therein is an exemplary combining of colinear edges according to Act 152 of method 140. …If the total distance of gaps 376 b and 376 c are less than the gross linear separation between edge 380 and 374 d (i.e. the gross linear separation is the distance between points 382 and 384), then edges 380, 374 b, 374 c and gaps 376 b, 376 c are replaced by a single spanning segment 386 on common line 378 as shown in polygon 372 c.”
, where “fill[ing] in gaps” between polygons is performing a union operation on the plurality of blocks (e.g., polygons) to generate a union block (e.g., single polygon such as depicted in Fig. 3I—not shown here)).
Since Hartfiel discloses performing a first morphological operation on the plurality of line segments generates a polygon (para(s). [0056]—see citation in limitation “performing a first morphological operation…” above), it would have been obvious to one of ordinary skill in the art before the effective filing date of the presently filed invention to modify the system of Hartfiel to incorporate generating a plurality of blocks by performing the first morphological information and performing a union operation on the plurality of blocks to generate a union block to repair discontinuities between polygons generated by the first morphological operation of dilation as taught by Hartfiel above (see para. [0073] above).
Regarding claim 2, Hartfiel discloses the contour line processing method of claim 1, wherein the first morphological operation is a dilation operation (para(s). [0056]—see citation in claim 1 limitation “performing a first morphological operation…” above).
Regarding claim 3, Hartfiel discloses the contour line processing method of claim 2, wherein the second morphological operation is an erosion operation (para(s). [0058]—see citation in claim 1 limitation “performing a second morphological operation…” above).
Regarding claim 4, Hartfiel discloses the contour line processing method of claim 3, wherein an erosion thickness of the erosion operation is less than or equal to a dilation width of the dilation operation (para(s). [0056] and [0058]—see citations in claim 1 limitations “performing a first morphological operation…” and “performing a second morphological operation…” above—, where the erosion thickness of the erosion operation is by “epsilon ε“ is the same as the dilation width of “ε>0” is the erosion thickness of the erosion operation being less than or equal to a dilation width of the dilation operation).
Regarding claim 5, Hartfiel discloses the contour line processing method of claim 1, wherein the step of determining the target contour block according to the processed block comprises detecting an outer contour of the processed block and determining the outer contour of the processed block as the target contour block (para(s). [0059] and [0064]—see citation in claim 1 limitation “determining a target contour block…”—, where the target contour block (e.g., the “true visual polygons”) is an outer contour (e.g., “polygon boundaries”) of the processed block (e.g., the “contracted visual polygons”)).
Regarding claim 6, the claim differs from claim 1 in that the claim is in the form of an electronic device comprising: a storage device, configured to store instructions; and a processing circuit, configured to execute the instructions of: the method of claim 1. Hartfiel discloses said electronic device comprising: a storage device, configured to store instructions; and a processing circuit (para(s). [0043] and [0098], recite(s)
[0043] “One or more systems described herein may be implemented in computer programs executing on programmable computers, each comprising at least one processor, a data storage system (including volatile and non-volatile memory and/or storage elements), at least one input device, and at least one output device. For example, and without limitation, the programmable computer may be a programmable logic unit, a mainframe computer, server, and personal computer, cloud-based program or system.”
[0098] “…The processor 204 may execute applications, computer readable instructions or programs. Applications may correspond with software modules comprising computer executable instructions to perform processing for the acts of methods 100, 140 and 160 described above. …”
, where the “data storage system” is a storage device and the “processor” or “programmable logic unit” is a processing circuit). Therefore, claim 6 recites similar limitations to claim 1 and is rejected for similar rationale and reasoning (see the analysis for claim 1 above).
Regarding claim 7, the claim recites similar limitations to claim 2 and is rejected for similar rationale and reasoning (see the analysis for claim 2 above).
Regarding claim 8, the claim recites similar limitations to claim 3 and is rejected for similar rationale and reasoning (see the analysis for claim 3 above).
Regarding claim 9, the claim recites similar limitations to claim 4 and is rejected for similar rationale and reasoning (see the analysis for claim 4 above).
Regarding claim 10, the claim recites similar limitations to claim 5 and is rejected for similar rationale and reasoning (see the analysis for claim 5 above).
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Wang (CN 108334879 A) discloses in the abstract and description, para. [0005]:
[abstract] “The present invention is applicable to the field of pattern recognition technology and provides a region extraction method, system and terminal device, including: reading an initial contour point set; sequentially filling and refining rectangular areas between two adjacent contour points in the initial contour point set to obtain single-pixel contour lines; obtaining a target area surrounded by the single-pixel contour lines; obtaining a rectangular region of interest based on the target area; and judging whether the rectangular region of interest is a target region of interest. This embodiment obtains a single-pixel contour line through filling and thinning processing, thereby overcoming the disadvantage of easy deformation and breakage; and this embodiment only needs to scan the image once when determining whether the rectangular region of interest is the target region of interest, avoiding repeated traversal, thereby greatly improving the efficiency of region extraction.”
[0005] “At present, morphological and mathematical methods are commonly used to extract contour points of arbitrary shape areas. However, the use of mathematical methods to connect contour points does not effectively utilize the morphological information of the contour in the image, the contour is easily deformed, and it is difficult to maintain the original shape of the complex contour; the morphological method needs to traverse the entire image, which is inefficient, and there are problems such as difficulty in selecting the size of structural elements, uneven thickness of the connected contour, or easy deformation and breakage.”
Lin et al. (CN 112991258 A) discloses in the abstract and description, para. [n0118]:
[abstract] “In an embodiment of the present invention, image information including an object to be detected is obtained, an image opening operation is performed on the image information to highlight the object to be detected, and object-highlighted image information is obtained; a straight line segment detection operation is performed on the object-highlighted image information using a straight line segment detection algorithm to determine all straight line segment objects in the object-highlighted image information; and a closed suppression combination algorithm is used to perform a straight line segment reconstruction operation on all the straight line segment objects to determine the object to be detected in the image information. It can be seen that the present invention can automatically perform image processing and object detection on image information to determine overlapping irregular non-closed objects in the image information. Compared with the algorithms in the prior art, the present invention has higher detection accuracy and efficiency for overlapping irregular non-closed objects, and can greatly reduce the investment of manpower and material resources, reduce the error rate, and improve the efficiency of drawing review.”
[n0118] “Specifically, the purpose of the above steps is to remove irrelevant objects from the original image.
Since the overlapping irregular non-closed objects discussed in the present invention are usually composed of regular straight line segments, removing irrelevant objects (such as text, tables, regular graphics, etc.) in the original image will help with subsequent detection work.
This is mainly accomplished by combining the morphological erosion and dilation operations in traditional image processing. Both erosion and dilation operations use pre-designed structural elements to perform sliding processing on binary images. Specifically:”
Shinagawa et al. (US 2009/0263000 A1) discloses in the abstract and para. [0041]:
[abstract] “Described herein is a method and system for facilitating computer-aided detection (CAD). In one implementation, image data is received (302) and iterations of an iterative segmentation process is performed on the image data. Each iterative segmentation process may include ascertaining whether a segment is normal (304), removing the segment from the image if ascertained to be normal (308) and transforming the shape of the segment (310). The iterative segmentation process may be stopped if a stop condition is met (312).”
[0041] “At step 310 , the shape of the segment is transformed to further refine the segmentation. In one implementation, the shape of the segment is transformed by performing at least one mathematical morphology operation on the image data. Other types of transformation operations, such as thinning and region growing, may also be performed. In one implementation, the morphology operation comprises merger or decomposition. Other types of morphology operations may also be used. Decomposition and merger operations may be performed alternately at step 310 . For example, if during the previous iteration cycle, decomposition was performed at step 310 , a merger will be performed during the current iteration cycle at step 310 . Conversely, if during the previous iteration cycle, merger was performed at step 310 , the current morphology operation is a decomposition operation. Other types of sequences are also useful.”
Rejeb Sfar et al. (US 2019/0205485 A1) discloses in the abstract and para. [0016]:
[abstract] “The disclosure notably relates to a computer-implemented method for generating a 3D model representing a building. The method comprises providing a 2D floor plan representing a layout of the building. The method also comprises determining a semantic segmentation of the 2D floor plan. The method also comprises determining the 3D model based on the semantic segmentation. Such a method provides an improved solution for processing a 2D floor plan.”
[0016] “…determining the mask for each respective class comprises an initialization with all pixels of the semantic segmentation corresponding to the respective class, a skeletonizing, and a merge of line segments to reduce the number of line segments;…”
Ishida et al. (US 2007/0230809 A1) discloses in the abstract and para. [0062]:
[abstract] “In an image processing method, contour information is extracted on the basis of terminal points and intersections included in a thinned line drawing, the contour information being extracted for each of closed curves and line elements connecting the terminal points and the intersections included in the line drawing, and skeletonized vector data is generated on the basis of the contour information. Start and end terminal points in the skeletonized vector data are determined. Artificial vectors to be inserted between the determined start and end terminal points are generated, and artificial-vector-inserted vector data including the generated artificial vectors is generated. A smoothing process is performed for the artificial-vector-inserted vector data, and then smoothed, non-circumference vector data is generated on the basis of the start and end terminal points. The thinned line drawing is raster-scanned in units of a pixel matrix.”
[0062] “Then, the thinned binary image is processed by a contour-vector-data extractor 300. More specifically, in a single raster scanning process of the thinned binary image, a group of vector sequences is extracted from a line drawing included in the thinned binary image, the vector sequences corresponding to closed curves and independent lines connecting terminal points and intersections in the line drawing. The group of vector sequences is hereinafter called “line-element coarse contour vector data”. Thus, a one-pixel-wide line drawing included in the thinned binary image is divided into line elements (straight lines or open curves) and closed curves on the basis of the terminal points and intersections in the line drawing. Then, each of the line elements and closed curves is subjected to a process of extracting a contour vector sequence that surrounds the line element or the closed curve.”
Weiss et al. (US 2023/0177224 A1) discloses in the abstract and para. [0094]:
[abstract] “Methods, systems, and apparatus, including medium-encoded computer program products, for computer aided design with feature thickness control, include: a three-dimensional modeling program configured to provide voxelized thinning based distance to medial surface processing that measures thicknesses in a three-dimensional model, and/or ramped scaling based thickness constraint application during shape and/or topology generation. The three-dimensional modeling program can be an architecture, engineering and/or construction program (e.g., building information management program), a product design and/or manufacturing program (e.g., a CAM program), and/or a media and/or entertainment production program (e.g., an animation production program).”
[0094] “Returning to FIG. 2 A, a voxelized line skeleton for the three-dimensional shape is computed 205 . This can be done using the Lee and Kashyap algorithm or using another thinning algorithm. In some implementations, the voxelized line skeleton includes one or more line segments that connect different portions of the three-dimensional shape with each other. For example, when there are one or more preserve regions, a voxelized line skeleton can be computed 205 in which the one or more preserve regions are required to be in the result, which means the produced line skeleton will connect with each of the one or more preserve regions. When there are no preserve regions, the computed 205 voxelized line skeleton is the line skeleton that remains after eroding all voxels on any branch that has an end, so as to keep any portions of the topology that connect other portions of the topology with each other, i.e., a loop connects different portions of the topology so it is needed to keep the shape as a cohesive whole, while eliminating regions of the line skeleton that form fingers or other “unimportant” features of the design.”
Deslandes et al. (US 2018/0075184 A1) discloses in the abstract and paras. [0097] and [0099]:
[abstract] “The invention notably relates to a computer-implemented method for designing a mechanical part, the method comprising: providing a subset of a finite element mesh (FEM), the subset of the FEM representing the mechanical part; and determining a representation of a skeleton of the mechanical part based on the subset of the FEM, the skeleton having branches and branch junctions, each branch junction joining respective branches. This improves the designing of a mechanical part.”
[0097] “In the context of the method, the dilation operation may be to add to the optimized mesh M all tetrahedrons of G−M adjacent to a boundary triangle of M. The resulting mesh is noted δ(M). The erosion operation may be to remove from a given mesh all tetrahedrons adjacent to a boundary triangle. It is noted ε(M). The regularization is ε(δ(M)). A regularized mesh M=ε(δ(M)) is stable in the following sense M′=ε(δ(M′)), meaning that regularizing a regular mesh yields the same mesh.”
[0099] “In practice, the dilation/erosion process can be implemented as follows. The dilation step is computed but the erosion step is included in the first iteration of the thinning process, explained in the following.”
Kakrana et al. (US 2021/0365679 A1) discloses in the abstract and para. [0043]:
[abstract] “A method of extracting information from a flowchart image comprising a plurality of closed-shaped data nodes having text enclosed within, connecting lines connecting the plurality of closed-shaped data nodes and free text adjacent to the connecting lines includes receiving the flowchart image, detecting the closed-shaped data nodes, localizing the text enclosed within the closed-shaped data nodes, and masking the localized text.to generate an annotated image. Lines in the annotated image are the detected to reconstruct them as closed-shaped data nodes and connecting lines. A tree frame with the plurality of closed-shaped data nodes and the connecting lines is extracted. The free text is then localized. Chunks of the free text oriented and positioned proximally together are assembled into text blocks using an orientation-based two-dimensional clustering.”
[0043] “The flowchart image 300 is initially converted into a desired image format (.png, .jpg, etc.), resized, denoised and sharpened before preprocessing. In some embodiments, the preprocessing involves one or more of: (i) image binarization (converting the flowchart image into a black-and-white image) using one or more of: simple binarization, adaptive binarization, and Otsu binarization, (ii) inversion of the flowchart image 300 to have a black background and white foreground objects, (iii) morphological transformation through one or more rounds of dilation to expand the white foreground objects using an appropriate structural element or kernel size, (iv) morphological transformation through one or more rounds of erosion to contract the white foreground objects using an appropriate structural element or kernel size, and (v) edge detection using canny edge detection algorithm to highlight the horizontal lines, vertical lines and edges pf the white foreground objects.”
Young et al. (US 2017/0249529 A1) discloses in the abstract and para. [0067]:
[abstract] “A computer-implemented image processing technique for selectively recovering the features of an original CAD model after the original CAD model has been converted to a digitized image and a new CAD model generated from the digitized image. The original boundary representation provides a template to transform the representation through processing under governance of a programmed processor so as to recover accuracy and reintroduce feature edges and feature corners as well as other detailed features to the CAD model obtained from the digitized image, e.g., to enable detailed features to be retained that would otherwise have been lost due to the lossy conversion into image space. The method operates to better ensure that reconstructed boundary vertices lie on original CAD model surfaces and feature edges and corners are recovered.”
[0067] “FIG. 1C shows a modified (i.e., digitally altered) version of the digitized representation of the object in the memory device as a result of the transformative techniques noted above. The purpose of the modification can be manifold. For example, the modification can be for healing invalid portions of the original CAD model. However, the modification process can also be used on valid CAD models, e.g., to defeature or edit the CAD to remove features that are unwanted or unnecessary for subsequent processing, or to perform Boolean operations with other images. These other images can themselves be digitized version of CAD models or they can be original digital data, e.g., obtained by a scanning a real object or physical volume. The modification step can thus be a technique for healing invalid CAD models, or for combining the original CAD model in some way with other image data, or simply for editing the original CAD model to prepare it for subsequent processing. In this example, the modification comprises removing (e.g., painting out) two small projections on a surface of the object. In other embodiments, other types of known image-based operators can be used, e.g., morphological operators (e.g., dilate, erode, close and open), manual painting, image filtering, etc. Localized smoothing or Boolean operations can be used to de-feature a geometry. Invalid portions of the original CAD model can be corrected in this manner.”
Gillies (“The Shapely User Manual,” 2013) discloses in the abstract and section “Linear Rings” on pg. 6 and Fig. 9 on pg. 24:
[abstract] “This document explains how to use the Shapely Python package for computational geometry.”
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Plettinck et al. (US 2021/0350037 A1) discloses in the abstract and para. [0056]:
[abstract] “A computer-implemented method for creating a computer-aided design (CAD) corresponding to a 2-dimensional rendering of an unfolded blank configured for manipulation into a 3-dimensional shape. The method includes obtaining a first digital, non-CAD design file containing information relating to the unfolded blank geometry but lacking metadata that defines cut or crease lines separately from surrounding content, and deriving, with a computer processor, a digital representation of the unfolded blank geometry based upon the first digital non-CAD design file. The digital representation includes defined data corresponding to a shape having one or more defined cut and/or crease lines. A system for performing the method includes a computer processor and machine-readable media accessible by the computer processor comprising non-transitory, instructions readable by the computer processor for performing the method steps of defining the digital non-CAD design file and deriving the digital representation therefrom.”
[0056] “The identified group is then processed in step 1150 to convert it to a mask, such as for example, performing the steps of: (1) rendering the group at a large DPI; (2) applying a flood fill on the outside of the box, and (3) inverting the flood-filled image. The foregoing steps result in a mask that may potentially still contain a few lines pointing outside. To remove additional lines in step 1160, the processor may apply a 1 pixel erosion followed by a 1 pixel dilation. The foregoing may be performed on a rastered image or a vector image, but if performed on a rastered image, the rastered image may then be vectorized, such as by any algorithm known in the art for such a purpose, including but not limited to the polygon-based tracing algorithm known as Potrace (Potrace: a polygon-based tracing algorithm, Peter Selinger Sep. 20, 2003; http://potrace.sourceforge.net/potrace.pdf), incorporated herein by reference.”
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/J.Z.Y./Examiner, Art Unit 2666
/EMILY C TERRELL/Supervisory Patent Examiner, Art Unit 2666