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 .
Response to Arguments
Applicant’s arguments, filed 5/6/2026, have been fully considered and the examiner’s responses are given below.
The claim objections are withdrawn, however new objections are presented below.
The 35 U.S.C. 112(b) rejections are withdrawn, however new rejections are presented below.
The 35 U.S.C. 101 rejections are not withdrawn.
In response to Applicant’s arguments about a particular machine, integrating the abstract idea into a practical application and an improvement, the Examiner respectfully disagrees. As there does not appear to be a specific argument made in this regard, no response is given herein, and the rejection is maintained.
The 35 U.S.C. 102/103 rejections are withdrawn, however new grounds are presented below.
Applicant’s amendments to the independent claims alter the scope of the claims, therefore new prior art has been applied. Applicant has not provided any arguments.
Claim Objections
Claim 1 and 18 are objected to because of the following informalities:
Regarding claims 1 and 18, “method in is” should read “method is”.
Appropriate correction is required.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 18 and 20-22 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Regarding claim 18, “the identification method” lacks antecedent basis, therefore this claim is indefinite. For the purposes of examination, Examiner has interpreted “the identification method” to mean the configured steps.
Regarding claims 20-22, these claims depend from claim 18 and are therefore rejected for the same reason as claim 18 above, as they do not cure the deficiencies of claim 18 noted above.
The following is a quotation of 35 U.S.C. 112(d):
(d) REFERENCE IN DEPENDENT FORMS.—Subject to subsection (e), a claim in dependent form shall contain a reference to a claim previously set forth and then specify a further limitation of the subject matter claimed. A claim in dependent form shall be construed to incorporate by reference all the limitations of the claim to which it refers.
The following is a quotation of pre-AIA 35 U.S.C. 112, fourth paragraph:
Subject to the following paragraph [i.e., the fifth paragraph of pre-AIA 35 U.S.C. 112], a claim in dependent form shall contain a reference to a claim previously set forth and then specify a further limitation of the subject matter claimed. A claim in dependent form shall be construed to incorporate by reference all the limitations of the claim to which it refers.
Claim 20 is rejected under 35 U.S.C. 112(d) or pre-AIA 35 U.S.C. 112, 4th paragraph, as being of improper dependent form for failing to further limit the subject matter of the claim upon which it depends, or for failing to include all the limitations of the claim upon which it depends.
Regarding claim 20, this claim depends from canceled claim 19. A claim cannot depend from a canceled claim. For the purposes of examination, Examiner has interpreted claim 20 to depend from claim 18.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1, 3-16 and 18, 20-22 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more.
Claims 1 and 18 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. Claim 18 recites:
“An identification system for vehicle parking space information fusion, comprising: a memory, configured to store parking space information, wherein the parking space information includes a plurality of entry corners and one or more entry lines; and a Neural Processing Unit, configured to: read the parking space information from the memory; process and match the plurality of entry corners and the one or more entry lines of the parking space information; fuse information corresponding to the plurality of entry corners and the one or more entry lines, and parking space statistics information is generated; and output the parking space statistics
The limitations of storing and reading parking space information, as drafted, are processes that, under their broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components. That is, other than reciting by a memory and neural processing unit, nothing in the claim elements precludes the steps from practically being performed in the mind. For example, the memory and neural processing unit storing and reading in the context of this claim encompasses the user manually performing the steps of remembering parking space information and recalling the information in his mind. If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas. Accordingly, the claim recites an abstract idea.
The limitations of processing and matching entry corners and entry lines, and fusing information to generate parking space statistics, as drafted, are also processes that, under their broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components. That is, other than reciting by a neural processing unit, nothing in the claim precludes the processing, matching, fusing, and generating from practically being performed in the human mind. For example, but for the by a neural processing unit language, the claim encompasses the user thinking and matching entry corners and entry lines and creating parking space statistics in his mind. Thus, these limitations are also mental processes.
The limitations of grouping entry corners, screening an entry corner, matching entry lines with entry corners, grouping entry lines, and collecting statistics about entry lines, as drafted, are also processes that, under their broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components. That is, other than reciting by a neural processing unit, nothing in the claim precludes the grouping, screening, matching, and collecting from practically being performed in the human mind. For example, but for the by a neural processing unit language, the claim encompasses the user thinking and grouping entry lines and entry corners, determining a representative entry corner, matching entry lines and entry corners, and determining statistics of the entry lines in his mind. Thus, these limitations are also mental processes.
This judicial exception is not integrated into a practical application. The claim recites using a memory and neural processing unit to perform storing, reading, processing, matching, fusing, generating, outputting, grouping, screening, and collecting. The memory and neural processing unit in these steps is recited at a high-level of generality (i.e., as a generic computer performing a generic computer function of storing, reading, processing, matching, fusing, generating, outputting, grouping, screening, and collecting) such that it amounts to no more than mere instructions to apply the exception using a generic computer component. Accordingly, this additional element does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. The claim is directed to an abstract idea.
The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. The additional elements of an identification system, a memory, and a neural processing unit to perform storing, reading, processing, matching, fusing, generating, outputting, grouping, screening, and collecting, amount to no more than mere instructions to apply the exception using generic computer components. Mere instructions to apply an exception using generic computer components cannot provide an inventive concept. The claim is not patent eligible.
Dependent claims 3-16 and 20-22 when analyzed as a whole, are held to be patent ineligible under 35 U.S.C. 101 because the additional recited limitation(s) fail(s) to establish that the claims are not directed to an abstract idea. The dependent claims introduce additional elements such as a flash memory, a read-only memory , a field-replaceable unit, an erasable programmable read-only memory, and a flash read-only memory, which amount to generic computer components. The additional elements in the dependent claims are not sufficient to amount to significantly more than the judicial exception for the same reasons as with claim 18.
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 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.
Claims 1, 5, 18, and 21-22 are rejected under 35 U.S.C. 103 as being unpatentable over Pang (US 20240092344 A1, cited in a previous office action) in view of Zhou (CN 116052461 A) and Adams (US 20210182596 A1, cited in a previous office action).
Regarding claim 1, Pang discloses an identification method for vehicle parking space information fusion (Paragraphs 0009-0011, 0027, 0093-0094; “The processing device may be a device having a central processing unit/processor (CPU) and/or a graphics processing unit (GPU). The processing device may be a terminal”);
wherein the identification method is configured for processing parking space information, the parking space information including a plurality of entry corners and one or more entry lines, and the identification method comprises (Paragraphs 0037-0038; “corner points of the parking space shown in the stitched look-around image may be identified firstly, for example, based on image grayscale, edge detection or machine learning. Then, a parking space entrance line may be constructed based on the corner points of the parking space”);
processing and matching the plurality of entry corners and the one or more entry lines of the parking space information (Paragraphs 0037-0038; “corner points of the parking space shown in the stitched look-around image may be identified firstly, for example, based on image grayscale, edge detection or machine learning. Then, a parking space entrance line may be constructed based on the corner points of the parking space”);
fusing information corresponding to the plurality of entry corners and the one or more entry lines, and parking space statistics information being generated (Paragraphs 0037-0039; “The parking space detection model trained in the embodiments of the present disclosure determines whether a parking space image represents a real parking space, and outputs a direction angle of the parking space in a case that the parking space image represents a real parking space”);
and outputting the parking space statistics information (Paragraphs 0037-0039; “The parking space detection model trained in the embodiments of the present disclosure determines whether a parking space image represents a real parking space, and outputs a direction angle of the parking space in a case that the parking space image represents a real parking space”);
the step of processing and matching the plurality of entry corners and the one or more entry lines of the parking space information comprises (Paragraphs 0037-0038);
matching the one or more entry lines with the representative entry corner (Paragraph 0037, 0041, 0060; “a parking space entrance line may be constructed based on the corner points of the parking space. Parking space separation lines respectively connected to two endpoints of the parking space entrance line may be determined based on the parking space entrance line and other corner points of the parking space”);
the one or more entry lines being grouped into one or more entry line clusters (Paragraphs 0037, 0041, 0060, 0068; entry line clusters is mapped to parking space entrance lines and parking space separation lines);
and the step of fusing the information corresponding to the plurality of entry corners and the one or more entry lines includes (Paragraphs 0037-0039);
collecting statistics on information about the one or more entry lines included in each of the one or more entry line clusters (Paragraphs 0037, 0041, 0060, 0068; “A line segment connecting corner points 1 and 2 is a parking space entrance line, and a line segment connecting corner points 1 and 4 and a line segment connecting corner points 2 and 3 are parking space separation lines”).
Pang does not teach a neural processing unit (NPU).
However, Zhou teaches applicable to a neural processing unit (Zhou - Page 63 Paragraph 2, Page 68 Paragraph 4) “NPU is neural network processor of the neural network”
a processing time of the Neural Processing Unit applying the identification method in is under 8 ms (Zhou - Page 63 Paragraph 2, Page 68 Paragraph 4) “fast processing the input information”; Additionally or alternatively, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to have a processing time of the identification method by the neural processing unit of under 8 milliseconds in the claimed manner since it has been held that discovering the optimum value of a result effective variable involves only routine skill in the art. Additionally, the specification does not explain why the processing time must be under 8 milliseconds in particular.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to modify the invention of Pang with a neural processing unit of Zhou with a reasonable expectation of success. One of ordinary skill in the art would understand that Zhou and Pang are both discuss parking space identification through machine learning. One would have been motivated to combine as this makes the processing speed faster while providing continuous self-learning (Zhou - Page 68 Paragraph 4).
Pang does not specifically state grouping the plurality of entry corners into a plurality of entry corner clusters; screening a representative entry corner included in each of the plurality of entry corner clusters; the representative entry corner in each of the plurality of entry corner clusters.
However, Adams teaches grouping the plurality of entry corners into a plurality of entry corner clusters (Paragraphs 0033-0035, 0088-0090, Fig. 6; “multiple points are included in the cluster representing estimated locations of the feature”);
screening a representative entry corner included in each of the plurality of entry corner clusters (Paragraph 0035; “a mode or mean of a cluster of points representing the feature may be used as the location of the feature (i.e., the landmark)”);
the representative entry corner in each of the plurality of entry corner clusters (Paragraph 0035; “a mode or mean of a cluster of points representing the feature may be used as the location of the feature (i.e., the landmark)”).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to modify the invention of Pang with creating entry corner clusters and screening a representative entry corner in each cluster of Adams with a reasonable expectation of success. One of ordinary skill in the art would understand that a vehicle is able to determine clusters of points on a feature and determine a mode or mean of the cluster of points for the best fit location of the feature. This allows the vehicle to localize itself and allows for trajectory planning such as parking maneuvers. One would have been motivated to combine Pang with Adams as this allows for robust parking systems. As stated in Adams, “The determined location may in some cases supplement other localization systems of the vehicle to provide accurate locations for trajectory planning and vehicle operations” (Paragraphs 0082-0083).
Regarding claim 5, Pang discloses the identification method further comprises (Paragraphs 0009-0011, 0093-0094).
Pang does not specifically state an attribute of each of the plurality of entry corners includes a probability value, and in the step of screening the plurality of entry corners included in each of the plurality of entry corner clusters for the representative entry corner; screening an entry corner of the plurality of entry corners with a maximum probability value as the representative entry corner based on a plurality of probability values of the plurality of entry corners included in each of the plurality of entry corner clusters.
However, Adams teaches an attribute of each of the plurality of entry corners includes a probability value, and in the step of screening the plurality of entry corners included in each of the plurality of entry corner clusters for the representative entry corner (Paragraphs 0033-0035; “Kalman filters”);
screening an entry corner of the plurality of entry corners with a maximum probability value as the representative entry corner based on a plurality of probability values of the plurality of entry corners included in each of the plurality of entry corner clusters (Paragraphs 0033-0035; “Kalman filters”).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to modify the invention of Pang with probability values of entry corners and a maximum probability as the representative entry corner of Adams with a reasonable expectation of success. One of ordinary skill in the art would understand that a cluster of feature points can represent a location of a feature, however not all the feature points may be accurate. Selecting a feature point with the highest probability can yield the most accurate location estimate. One would have been motivated to combine Pang with Adams as this achieves accurate location determination and trajectory planning. As stated in Adams, “The additional points may be projected onto the image 200 in order to combine the multiple measurements to reduce a level of uncertainty associated with the landmark” (Paragraph 0033).
Regarding claim 18, Pang discloses an identification system for vehicle parking space information fusion, comprising: a memory (Paragraphs 0088-0096; “The computer readable storage medium stores a computer program for performing the method for detecting a parking place and a direction angle of the parking place according the above embodiments”);
wherein the parking space information includes a plurality of entry corners and one or more entry lines (Pang - Paragraphs 0037-0038) “corner points of the parking space shown in the stitched look-around image may be identified firstly, for example, based on image grayscale, edge detection or machine learning. Then, a parking space entrance line may be constructed based on the corner points of the parking space”
read the parking space information from the memory (Paragraph 0030; “The server 101 is connected to a sample database 103, and the server 101 may obtain a training sample from the sample data 103”).
process and match the plurality of entry corners and the one or more entry lines of the parking space information (Pang - Paragraphs 0037-0038) “ corner points of the parking space shown in the stitched look-around image may be identified firstly, for example, based on image grayscale, edge detection or machine learning. Then, a parking space entrance line may be constructed based on the corner points of the parking space”
fuse information corresponding to the plurality of entry corners and the one or more entry lines, and parking space statistics information is generated (Pang - Paragraphs 0037-0039) “The parking space detection model trained in the embodiments of the present disclosure determines whether a parking space image represents a real parking space, and outputs a direction angle of the parking space in a case that the parking space image represents a real parking space”
output the parking space statistics information (Pang - Paragraphs 0037-0039) “The parking space detection model trained in the embodiments of the present disclosure determines whether a parking space image represents a real parking space, and outputs a direction angle of the parking space in a case that the parking space image represents a real parking space”
match the one or more entry lines with each representative entry corner (Pang - Paragraph 0037, 0041, 0060) “a parking space entrance line may be constructed based on the corner points of the parking space. Parking space separation lines respectively connected to two endpoints of the parking space entrance line may be determined based on the parking space entrance line and other corner points of the parking space”
and the one or more entry lines are grouped into one or more entry line clusters (Pang - Paragraphs 0037, 0041, 0060, 0068) entry line clusters is mapped to parking space entrance lines and parking space separation lines
and collect statistics on information about the one or more entry lines included in each of the one or more entry line clusters (Pang - Paragraphs 0037, 0041, 0060, 0068) “A line segment connecting corner points 1 and 2 is a parking space entrance line, and a line segment connecting corner points 1 and 4 and a line segment connecting corner points 2 and 3 are parking space separation lines”
Pang does not teach a neural processing unit.
However, Zhou teaches a neural processing unit, configured to (Zhou - Page 63 Paragraph 2, Page 68 Paragraph 4) “NPU is neural network processor of the neural network”
wherein a processing time of the Neural Processing Unit applying the identification method in is under 8 ms (Zhou - Page 63 Paragraph 2, Page 68 Paragraph 4) “fast processing the input information”; Additionally or alternatively, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to have a processing time of the identification method by the neural processing unit of under 8 milliseconds in the claimed manner since it has been held that discovering the optimum value of a result effective variable involves only routine skill in the art. Additionally, the specification does not explain why the processing time must be under 8 milliseconds in particular.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to modify the invention of Pang with a neural processing unit of Zhou with a reasonable expectation of success. One of ordinary skill in the art would understand that Zhou and Pang are both discuss parking space identification through machine learning. One would have been motivated to combine as this makes the processing speed faster while providing continuous self-learning (Zhou - Page 68 Paragraph 4).
Pang does not teach group the plurality of entry corners into a plurality of entry corner clusters; screen a representative entry corner included in each of the plurality of entry corner clusters.
However, Adams teaches group the plurality of entry corners into a plurality of entry corner clusters (Adams - Paragraphs 0033-0035, 0088-0090, Fig. 6) “multiple points are included in the cluster representing estimated locations of the feature”
screen a representative entry corner included in each of the plurality of entry corner clusters (Adams - Paragraph 0035) “a mode or mean of a cluster of points representing the feature may be used as the location of the feature (i.e., the landmark)”
It would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to modify the invention of Pang with creating entry corner clusters and screening a representative entry corner in each cluster of Adams with a reasonable expectation of success. One of ordinary skill in the art would understand that a vehicle is able to determine clusters of points on a feature and determine a mode or mean of the cluster of points for the best fit location of the feature. This allows the vehicle to localize itself and allows for trajectory planning such as parking maneuvers. One would have been motivated to combine Pang with Adams as this allows for robust parking systems. As stated in Adams, “The determined location may in some cases supplement other localization systems of the vehicle to provide accurate locations for trajectory planning and vehicle operations” (Paragraphs 0082-0083).
Regarding claim 21, Pang discloses the memory is a flash memory, a read-only memory or a field-replaceable unit (Pang - Paragraph 0101) “The storage medium described above includes various media storing program codes, such as a USB flash disk, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a disk, or an optical disc”
Regarding claim 22, Pang does not teach the read-only memory is an erasable programmable read-only memory or a flash read-only memory.
However, Zhou teaches the read-only memory is an erasable programmable read-only memory or a flash read-only memory (Zhou - Page 60 Paragraph 4) “can also be an electrically erasable programmable read only memory (EEPROM)”
It would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to modify the invention of Pang with an erasable programmable read-only memory of Zhou with a reasonable expectation of success. One of ordinary skill in the art would understand that Pang and Zhou both describe vehicle parking space identification programs. One would have been motivated to combine as this improves the application range of the parking space identification method (Zhou – Page 2 Paragraph 5 – Page 3 Paragraph 1).
Claims 3, 12, and 20 are rejected under 35 U.S.C. 103 as being unpatentable over Pang, Zhou, and Adams, as applied to claims 1 and 18 above, and further in view of Liu (US 20220198928 A1, cited in a previous office action).
Regarding claim 3, Pang discloses and an attribute (Paragraphs 0037-0041; “A line segment connecting corner points 1 and 2 is a parking space entrance line, and a line segment connecting corner points 1 and 4 and a line segment connecting corner points 2 and 3 are parking space separation lines. In addition, it is labeled that the parking space label labels a real parking space, and a direction angle of the parking space is labeled”);
and the identification method further comprises (Paragraphs 0009-0011, 0093-0094);
matching the one or more entry lines with the representative entry corner of the plurality of entry corner clusters (Paragraph 0037, 0041, 0060; “a parking space entrance line may be constructed based on the corner points of the parking space. Parking space separation lines respectively connected to two endpoints of the parking space entrance line may be determined based on the parking space entrance line and other corner points of the parking space”);
and the one or more entry lines into the one or more entry line clusters being grouped, wherein each of the one or more entry line clusters includes two representative entry corners and one or more entry lines (Paragraph 0037, 0041; “a line segment connecting the left corner points 1 and 2 as a parking space entrance line and taking a line segment connecting the left corner points 1 and 4 and a line segment connecting the left corner points 2 and 3 as parking space separation lines”);
and collecting statistics based on the attribute of each of the one or more entry lines included in each of the one or more entry line clusters, to respectively define a representative attribute for each of the one or more entry line clusters (Paragraphs 0037-0041; “A line segment connecting corner points 1 and 2 is a parking space entrance line, and a line segment connecting corner points 1 and 4 and a line segment connecting corner points 2 and 3 are parking space separation lines. In addition, it is labeled that the parking space label labels a real parking space, and a direction angle of the parking space is labeled”).
Pang does not specifically state each of the plurality of entry corners includes coordinates and an attribute; grouping the plurality of entry corners into the plurality of entry corner clusters based on the coordinates of each of the plurality of entry corners; screening the plurality of entry corners included in each of the plurality of entry corner clusters for the representative entry corner; of the plurality of entry corner clusters.
However, Adams teaches each of the plurality of entry corners includes coordinates and an attribute (Paragraphs 0020, 0024, 0034; “an image coordinate associated with a location of the feature within the image may be determined”);
grouping the plurality of entry corners into the plurality of entry corner clusters based on the coordinates of each of the plurality of entry corners (Paragraphs 0024, 0033-0035, 0088-0090, Fig. 6; “multiple points are included in the cluster representing estimated locations of the feature”);
screening the plurality of entry corners included in each of the plurality of entry corner clusters for the representative entry corner (Paragraph 0034-0035; “a mode or mean of a cluster of points representing the feature may be used as the location of the feature (i.e., the landmark)”);
of the plurality of entry corner clusters (Paragraphs 0033-0035, 0088-0090, Fig. 6; “the clusters 204, 206, and/or 208 may be used to refine the location of the feature”).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to modify the invention of Pang with entry corners includes coordinates and an attribute, creating entry corner clusters, and screening a representative entry corner in each cluster of Adams with a reasonable expectation of success. One of ordinary skill in the art would understand that a vehicle is able to determine clusters of points on a feature and determine a mode or mean of the cluster of points for the best fit location of the feature. This allows the vehicle to localize itself and allows for trajectory planning such as parking maneuvers. One would have been motivated to combine Pang with Adams as this allows for robust parking systems. As stated in Adams, “The determined location may in some cases supplement other localization systems of the vehicle to provide accurate locations for trajectory planning and vehicle operations” (Paragraphs 0082-0083).
Pang does not specifically state each of the one or more entry lines includes coordinates; based on the coordinates of each of the one or more entry lines; the coordinates and representative coordinates.
However, Liu teaches each of the one or more entry lines includes coordinates (Paragraph 0068; “By identifying the world coordinates of the boundary lines 212 and applying the line rule 120 based on those coordinates, the parking space 202 of FIG. 2 can be identified”);
based on the coordinates of each of the one or more entry lines (Paragraph 0068; “By identifying the world coordinates of the boundary lines 212 and applying the line rule 120 based on those coordinates, the parking space 202 of FIG. 2 can be identified”);
the coordinates and representative coordinates (Paragraph 0068; “By identifying the world coordinates of the boundary lines 212 and applying the line rule 120 based on those coordinates, the parking space 202 of FIG. 2 can be identified”).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to modify the invention of Pang with coordinates and representative coordinates of the entry lines of Liu with a reasonable expectation of success. One of ordinary skill in the art would understand that determining coordinates of the entry lines allows the parking space to be identified based on line rules. Lengths and endpoints can be calculated to determine the geometry of the parking space. One would have been motivated to combine Pang with Liu as this achieves identifying the parking space. As stated in Liu, “By identifying the world coordinates of the boundary lines 212 and applying the line rule 120 based on those coordinates, the parking space 202 of FIG. 2 can be identified” (Paragraph 0068).
Regarding claim 12, Pang discloses and an attribute (Paragraphs 0041-0044; “a horizontal parking space, a vertical parking space, an oblique parking space or a non-real parking space”);
the attribute of each of the one or more entry lines comprises a parking space type (Paragraphs 0041-0044; “a horizontal parking space, a vertical parking space, an oblique parking space or a non-real parking space”);
and the identification method further comprises (Paragraphs 0009-0011, 0093-0094);
finding a first mode based on the parking space type of the one or more entry lines included in each of the one or more entry line clusters (Paragraphs 0067-0068; “display a designated type of parking space in a highlight mode in displaying the parking space detection result”);
and a representative parking space type of each of the one or more entry line clusters being defined (Paragraphs 0041-0044; “a horizontal parking space, a vertical parking space, an oblique parking space or a non-real parking space”).
Pang does not specifically state each of the one or more entry lines includes coordinates.
However, Liu teaches each of the one or more entry lines includes coordinates (Paragraph 0068; “By identifying the world coordinates of the boundary lines 212 and applying the line rule 120 based on those coordinates, the parking space 202 of FIG. 2 can be identified”).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to modify the invention of Pang with coordinates of the entry lines of Liu with a reasonable expectation of success. One of ordinary skill in the art would understand that determining coordinates of the entry lines allows the parking space to be identified based on line rules. Lengths and endpoints can be calculated to determine the geometry of the parking space. One would have been motivated to combine Pang with Liu as this achieves identifying the parking space. As stated in Liu, “By identifying the world coordinates of the boundary lines 212 and applying the line rule 120 based on those coordinates, the parking space 202 of FIG. 2 can be identified” (Paragraph 0068).
Regarding claim 20, all of the limitations have been examined with respect to claim 3. Please see the rejection above.
Claim 4 is rejected under 35 U.S.C. 103 as being unpatentable over Pang, Zhou, and Adams, as applied to claim 1 above, and further in view of Kim (US 20240193786 A1, cited in a previous office action).
Regarding claim 4, Pang discloses the identification method further comprises (Paragraphs 0009-0011, 0093-0094).
Pang does not specifically state in the step of grouping the plurality of entry corners into the plurality of entry corner clusters based on the coordinates of each of the plurality of entry corners; determining whether a distance between any two entry corners is less than a first distance threshold, in response to the distance between any two entry corners is less than a first distance threshold, grouping the any two of the plurality of entry corners into a same entry corner cluster.
However, Kim teaches in the step of grouping the plurality of entry corners into the plurality of entry corner clusters based on the coordinates of each of the plurality of entry corners (Paragraphs 0073, 0089; “identify whether the distance between the points in the ROI is within the predetermined threshold distance. The distance identification module 1303 may assign a cluster index to points within the predetermined threshold distance”);
determining whether a distance between any two entry corners is less than a first distance threshold, in response to the distance between any two entry corners is less than a first distance threshold, grouping the any two of the plurality of entry corners into a same entry corner cluster (Paragraphs 0073, 0089; “identify whether the distance between the points in the ROI is within the predetermined threshold distance. The distance identification module 1303 may assign a cluster index to points within the predetermined threshold distance”).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to modify the invention of Pang with grouping corner points into clusters based on the distance between points less than a threshold of Kim with a reasonable expectation of success. One of ordinary skill in the art would understand that by extracting corner points of features and grouping them into clusters based on distance, different features can be extracted. Points that are close together are grouped into a cluster and represent a feature, while points far apart represent different objects. One would have been motivated to combine Pang with Kim as this improves vehicle recognition of surroundings. As stated in Kim, “recognizing a space capable of improving the performance of recognizing a surrounding space of a vehicle, for example, a parking space” (Paragraph 0009).
Claim 9 is rejected under 35 U.S.C. 103 as being unpatentable over Pang, Zhou, and Adams, as applied to claim 1 above, and further in view of Liu (US 20220198928 A1, cited in a previous office action) and Kim (US 20240193786 A1, cited in a previous office action).
Regarding claim 9, Pang discloses each of the one or more entry lines includes an attribute (Paragraphs 0037-0041; “A line segment connecting corner points 1 and 2 is a parking space entrance line, and a line segment connecting corner points 1 and 4 and a line segment connecting corner points 2 and 3 are parking space separation lines. In addition, it is labeled that the parking space label labels a real parking space, and a direction angle of the parking space is labeled”);
the entry lines comprise two endpoints, and in the step of matching the one or more entry lines with the representative entry corner based on the one or more entry lines (Paragraph 0037, 0041, 0060; “a parking space entrance line may be constructed based on the corner points of the parking space. Parking space separation lines respectively connected to two endpoints of the parking space entrance line may be determined based on the parking space entrance line and other corner points of the parking space”).
in the step of matching the one or more entry lines with the representative entry corner based on the one or more entry lines (Paragraph 0037, 0041, 0060; “a parking space entrance line may be constructed based on the corner points of the parking space. Parking space separation lines respectively connected to two endpoints of the parking space entrance line may be determined based on the parking space entrance line and other corner points of the parking space”);
the one or more entry lines being grouped into the one or more entry line clusters (Paragraphs 0037, 0041, 0060, 0068; entry line clusters is mapped to parking space entrance lines and parking space separation lines);
the identification method further comprises (Paragraphs 0009-0011, 0093-0094).
Pang does not specifically state in each of the plurality of entry corner clusters.
However, Adams teaches in each of the plurality of entry corner clusters (Paragraphs 0033-0035, 0088-0090, Fig. 6; “the clusters 204, 206, and/or 208 may be used to refine the location of the feature”).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to modify the invention of Pang with a plurality of entry corner clusters of Adams with a reasonable expectation of success. One of ordinary skill in the art would understand that a vehicle is able to determine clusters of points on a feature and determine a mode or mean of the cluster of points for the best fit location of the feature. This allows the vehicle to localize itself and allows for trajectory planning such as parking maneuvers. One would have been motivated to combine Pang with Adams as this allows for robust parking systems. As stated in Adams, “The determined location may in some cases supplement other localization systems of the vehicle to provide accurate locations for trajectory planning and vehicle operations” (Paragraphs 0082-0083).
Pang does not specifically state entry line coordinates.
However, Liu teaches entry line coordinates (Paragraph 0068; “By identifying the world coordinates of the boundary lines 212 and applying the line rule 120 based on those coordinates, the parking space 202 of FIG. 2 can be identified”).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to modify the invention of Pang with coordinates of the entry lines of Liu with a reasonable expectation of success. One of ordinary skill in the art would understand that determining coordinates of the entry lines allows the parking space to be identified based on line rules. Lengths and endpoints can be calculated to determine the geometry of the parking space. One would have been motivated to combine Pang with Liu as this achieves identifying the parking space. As stated in Liu, “By identifying the world coordinates of the boundary lines 212 and applying the line rule 120 based on those coordinates, the parking space 202 of FIG. 2 can be identified” (Paragraph 0068).
Pang does not specifically state determining that a distance between one endpoint of any of the one or more entry lines and any of the representative entry corner of the plurality of entry corner clusters is less than a second distance threshold; and matching the any of the one or more entry lines with the any of the representative entry corner of the plurality of entry corner clusters, and the any of the one or more entry lines being grouped into a same entry line cluster.
However, Kim teaches determining that a distance between one endpoint of any of the one or more entry lines and any of the representative entry corner of the plurality of entry corner clusters is less than a second distance threshold (Paragraphs 0101-0103, Fig. 4; “When the distance between the segment and the corner point is equal to or less than the predetermined threshold distance”);
and matching the any of the one or more entry lines with the any of the representative entry corner of the plurality of entry corner clusters, and the any of the one or more entry lines being grouped into a same entry line cluster (Paragraphs 0116-0118, Fig. 4; “generate the L-shaped contour including all the cluster points based on the X-axis maximum coordinate value and the Y-axis minimum coordinate value of the cluster points and the X-axis maximum coordinate value and the Y-axis minimum coordinate value of the cluster points”).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to modify the invention of Pang with matching endpoints of entry lines with entry corners based on distance less than a second threshold of Kim with a reasonable expectation of success. One of ordinary skill in the art would understand that contours of an object can be extracted based on entry corner points and lines. When the distance between the corner point and endpoints of entry lines are less than a certain distance, a l-shaped contour can be fit to recognize the parking space. One would have been motivated to combine Pang with Kim as this achieves improved surrounding recognition of a vehicle. As stated in Kim, “recognizing a space capable of improving the performance of recognizing a surrounding space of a vehicle, for example, a parking space, by conservatively extracting contours of surrounding objects of the vehicle” (Paragraph 0009).
Claim 13 is rejected under 35 U.S.C. 103 as being unpatentable over Pang, Adams, and Liu, as applied to claim 12 above, and further in view of Chen (US 20250086983 A1, cited in a previous office action).
Regarding claim 13, Pang discloses the identification method further comprises (Paragraphs 0009-0011, 0093-0094);
entry line clusters (Paragraphs 0037, 0041, 0060, 0068).
Pang does not specifically state the attribute of the entry line includes an occupancy state; finding a second mode based on an occupancy state of the one or more entry lines included in each of the one or more entry line clusters; and a representative occupancy state of each of the one or more entry lines being defined.
However, Chen teaches the attribute of the entry line includes an occupancy state (Paragraphs 0015-0017, 0068, 0075-0076; “obtain information about whether the target parking space is occupied”);
finding a second mode based on an occupancy state of the one or more entry lines included in each of the one or more entry line clusters (Paragraph 0085; “automatic parking function of the automobile”);
and a representative occupancy state of each of the one or more entry lines being defined (Paragraphs 0015-0017, 0068, 0075-0076; “obtain information about whether the target parking space is occupied”).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to modify the invention of Pang with occupancy states of entry lines and finding a second mode based on an occupancy state of Chen with a reasonable expectation of success. One of ordinary skill in the art would understand that autonomous vehicles need to detect whether a parking space is occupied by another vehicle. This allows the vehicle to determine whether a parking space is valid and can be parked. One would have been motivated to combine Pang with Chen as this achieves improving driverless vehicle parking detection. As stated in Chen, “An effect of parking space detection greatly affects safety and stability of a parking process. Through the parking space detection technology, a driverless vehicle is able to obtain information of surrounding parking spaces in real time according to parking space marking lines on a parking lot and accurately judge whether a parking space thereof is valid or not” (Paragraph 0003).
Claim 14 is rejected under 35 U.S.C. 103 as being unpatentable over Pang, Zhou, and Adams, as applied to claim 1 above, and further in view of Liu (US 20220198928 A1, cited in a previous office action) and Lee (US 20250269842 A1, cited in a previous office action).
Regarding claim 14, Pang discloses an attribute (Paragraphs 0037-0041; “A line segment connecting corner points 1 and 2 is a parking space entrance line, and a line segment connecting corner points 1 and 4 and a line segment connecting corner points 2 and 3 are parking space separation lines. In addition, it is labeled that the parking space label labels a real parking space, and a direction angle of the parking space is labeled”);
the coordinates of the entry line include two endpoints (Paragraph 0037, 0041, 0060; “Parking space separation lines respectively connected to two endpoints”);
an attribute of the entry corner includes a parking space angle (Paragraphs 0039, 0068-0069; “a direction angle of the parking space”);
and the identification method further comprises (Paragraphs 0009-0011, 0093-0094).
Pang does not specifically state each of the one or more entry lines includes coordinates.
However, Liu teaches each of the one or more entry lines includes coordinates (Paragraph 0068; “By identifying the world coordinates of the boundary lines 212 and applying the line rule 120 based on those coordinates, the parking space 202 of FIG. 2 can be identified”).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to modify the invention of Pang with coordinates of the entry lines of Liu with a reasonable expectation of success. One of ordinary skill in the art would understand that determining coordinates of the entry lines allows the parking space to be identified based on line rules. Lengths and endpoints can be calculated to determine the geometry of the parking space. One would have been motivated to combine Pang with Liu as this achieves identifying the parking space. As stated in Liu, “By identifying the world coordinates of the boundary lines 212 and applying the line rule 120 based on those coordinates, the parking space 202 of FIG. 2 can be identified” (Paragraph 0068).
Pang does not specifically state calculating an average based on the parking space angles of two representative entry corners respectively paired with the two endpoints of each of the one or more entry lines, and a representative parking space angle of each of the one or more entry line clusters being defined.
However, Lee teaches calculating an average based on the parking space angles of two representative entry corners respectively paired with the two endpoints of each of the one or more entry lines, and a representative parking space angle of each of the one or more entry line clusters being defined (Paragraphs 0072-0075; “calculates the average angle (e.g., an average value) of the first angle and the second angle”).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to modify the invention of Pang with calculating an average of two parking space angles of Lee with a reasonable expectation of success. One of ordinary skill in the art would understand that the average 2 adjacent internal angles of a parking space should be 90 degrees. This allows the vehicle to determine whether it can determine the gradient/incline of the parking space, and control the driving torque. One would have been motivated to combine Pang with lee as this achieves improved performance of parking assistance. As stated in Lee, “This is for the purpose of performing longitudinal driving and braking control of the vehicle according to the gradient of the parking space to improve the performance of the parking assistance system” (Paragraph 0067).
Claim 15 is rejected under 35 U.S.C. 103 as being unpatentable over Pang, Zhou, Adams, Liu, and Lee, as applied to claim 14 above, and further in view of Heo (US 20250263069 A1, cited in a previous office action).
Regarding claim 15, Pang discloses the attribute of the entry line includes a parking space type (Paragraphs 0041-0044; “a horizontal parking space, a vertical parking space, an oblique parking space or a non-real parking space”);
and the identification method further comprises (Paragraphs 0009-0011, 0093-0094);
finding a mode based on a parking space type of the one or more entry lines included in each of the one or more entry line clusters (Paragraphs 0067-0068; “display a designated type of parking space in a highlight mode in displaying the parking space detection result”);
and a representative parking space type of each of the one or more entry line clusters being defined (Paragraphs 0041-0044; “a horizontal parking space, a vertical parking space, an oblique parking space or a non-real parking space”);
defining the representative parking space angle of each of the one or more entry line clusters as 90 degrees when it is determined that the representative parking space type does not belong to the slant parking space (Paragraphs 0041-0043, 0067; “the parking space label may identify that the real parking space is a vertical parking space, a parallel parking space or an oblique parking space”).
Pang does not specifically state calculating an average based on the parking space angles of the two representative entry corners respectively paired with the two endpoints of each of the one or more entry lines when the representative parking space angle for each of the one or more entry line clusters being defined.
However, Lee teaches calculating an average based on the parking space angles of the two representative entry corners respectively paired with the two endpoints of each of the one or more entry lines when the representative parking space angle for each of the one or more entry line clusters being defined (Paragraphs 0072-0075; “calculates the average angle (e.g., an average value) of the first angle and the second angle”).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to modify the invention of Pang with calculating an average of two parking space angles of Lee with a reasonable expectation of success. One of ordinary skill in the art would understand that the average 2 adjacent internal angles of a parking space should be 90 degrees. This allows the vehicle to determine whether it can determine the gradient/incline of the parking space, and control the driving torque. One would have been motivated to combine Pang with lee as this achieves improved performance of parking assistance. As stated in Lee, “This is for the purpose of performing longitudinal driving and braking control of the vehicle according to the gradient of the parking space to improve the performance of the parking assistance system” (Paragraph 0067).
Pang does not specifically state when it is determined that the representative parking space type belongs to a slant parking space.
However, Heo teaches when it is determined that the representative parking space type belongs to a slant parking space (Paragraph 0073; “When the type of the parking space 220 is diagonal parking, the determination unit 110 calculates a diagonal parking angle”).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to modify the invention of Pang with determining the parking space angle when the parking space is a slant parking type of Heo with a reasonable expectation of success. One of ordinary skill in the art would understand that when the vehicle knows it is in a slant parking, the parking angle can be calculated. When a vehicle is reversing out of a slant parking spot, the rear collision avoidance system detection area may need to be adjusted based on the angle of the parking spot. One would have been motivated to combine Pang with Heo as this achieves safer reversing out of parking spots. As stated in Heo, “the radar detection area of RCCA may need to be optimized according to the type of parking space” (Paragraph 0035).
Allowable Subject Matter
Claims 6-8, 10-11, and 16 would be allowable if rewritten to overcome the rejection(s) under 35 U.S.C. 101, set forth in this Office action and to include all of the limitations of the base claim and any intervening claims.
The following is a statement of reasons for the indication of allowable subject matter:
Claim 6 recites (emphasis added):
“The identification method of claim 5, wherein each of the one or more entry lines includes coordinates and an attribute, the coordinates of each of the one or more entry lines include two endpoints, and after the step of matching the one or more entry lines with the representative entry corner in each of the plurality of entry corner clusters based on the coordinates of each of the one or more entry lines, the one or more entry lines being grouped into the one or more entry line clusters, the identification method further comprises:
retaining one of two of the one or more entry lines, when it is determined that any of the representative entry corner of the plurality of entry corner clusters is paired with one endpoint of each one of the two of the one or more entry lines, wherein a probability value of another representative entry corner of the plurality of entry corner clusters paired with the other endpoint of one of the two of the one or more entry lines entry line retained is greater than a probability value of another representative entry corner paired with the other endpoint of one of the two of the one or more entry lines entry line not retained”.
The prior art does not teach, disclose, or otherwise render obvious the above-noted features of the claims.
Pang (US 20240092344 A1) discloses matching the entry corners and the entry lines (Paragraphs 0037-0038; “corner points of the parking space shown in the stitched look-around image may be identified firstly, for example, based on image grayscale, edge detection or machine learning. Then, a parking space entrance line may be constructed based on the corner points of the parking space”).
However, Pang does not specifically state a probability of entry corners paired with endpoints of the entry line.
Zhang (US 20200152060 A1) teaches performing probability Hough transform to detect a line segment set (Claim 18; “performing probability Hough transform to detect a line segment set”).
However, Zhang does not specifically state a probability of entry corners paired with endpoints of the entry line.
These differences between the subject matter of claim 6 and the prior art are not taught or otherwise rendered obvious by any available evidence in the remaining prior art. Accordingly, claim 6 recites allowable subject matter.
Claims 7-8 recite allowable subject matter based upon their dependency from claim 6.
The following is a statement of reasons for the indication of allowable subject matter:
Claim 10 recites (emphasis added):
“The identification method of claim 9, wherein in the step of matching the one or more entry lines with the representative entry corner in each of the plurality of entry corner clusters based on the coordinates of the one or more entry lines, the one or more entry lines being grouped into the one or more entry line clusters, the identification method further comprises:
determining whether the two endpoints of any of the one or more entry lines are not paired with the representative entry corner, in response to the two endpoints of any of the one or more entry lines are not paired with the representative entry corner, excluding the entry line”.
The prior art does not teach, disclose, or otherwise render obvious the above-noted features of the claims.
Pang (US 20240092344 A1) discloses matching the entry corners and the entry lines (Paragraphs 0037-0038; “corner points of the parking space shown in the stitched look-around image may be identified firstly, for example, based on image grayscale, edge detection or machine learning. Then, a parking space entrance line may be constructed based on the corner points of the parking space”).
However, Pang does not specifically state excluding entry lines.
Kim (US 20240193786 A1) teaches determining line segments when the distance between corners and lines are more and less than a certain distance (both paired and not paired) (Paragraph 0068, Fig. 4).
However, Kim does not specifically state determining whether the two endpoints of a line segment are not paired with the representative entry corner.
These differences between the subject matter of claim 10 and the prior art are not taught or otherwise rendered obvious by any available evidence in the remaining prior art. Accordingly, claim 10 recites allowable subject matter.
The following is a statement of reasons for the indication of allowable subject matter:
Claim 11 recites (emphasis added):
“The identification method of claim 9, wherein in the step of matching the one or more entry lines with the representative entry corner in each of the plurality of entry corner clusters based on the coordinates of the one or more entry lines, the one or more entry lines being grouped into the one or more entry line clusters, the identification method further comprises determining whether the two endpoints of any of the one or more entry lines are both paired with a same representative entry corner, in response to the two endpoints of any of the one or more entry lines are both paired with the representative entry corner, excluding any of the one or more entry lines”.
The prior art does not teach, disclose, or otherwise render obvious the above-noted features of the claims.
Pang discloses matching the entry corners and the entry lines (Paragraphs 0037-0038; “corner points of the parking space shown in the stitched look-around image may be identified firstly, for example, based on image grayscale, edge detection or machine learning. Then, a parking space entrance line may be constructed based on the corner points of the parking space”).
However, Pang does not specifically state determining whether the two endpoints of an entry line are both paired with a same representative entry corner.
These differences between the subject matter of claim 11 and the prior art are not taught or otherwise rendered obvious by any available evidence in the remaining prior art. Accordingly, claim 11 recites allowable subject matter.
The following is a statement of reasons for the indication of allowable subject matter:
Claim 16 recites (emphasis added):
“The identification method of claim 1, wherein each of the one or more entry lines includes coordinates and an attribute, the coordinates of each of the one or more entry lines include two endpoints, and the identification method further comprises:
replacing the two endpoints based on coordinates of two representative entry corners respectively paired with the two endpoints of each of the one or more entry lines, representative coordinates for each of the one or more entry line clusters being defined”.
The prior art does not teach, disclose, or otherwise render obvious the above-noted features of the claims.
Pang discloses matching the entry corners and the entry lines (Paragraphs 0037-0038; “corner points of the parking space shown in the stitched look-around image may be identified firstly, for example, based on image grayscale, edge detection or machine learning. Then, a parking space entrance line may be constructed based on the corner points of the parking space”).
However, Pang does not specifically state replacing the two endpoints of an entry line.
Xiao (US 20200130696 A1) teaches replacing one end point on the segment with another end point (Paragraph 0204).
However, Xiao does not specifically state replacing the two endpoints of a segment.
These differences between the subject matter of claim 16 and the prior art are not taught or otherwise rendered obvious by any available evidence in the remaining prior art. Accordingly, claim 16 recites allowable subject matter.
Any comments considered necessary by applicant must be submitted no later than the payment of the issue fee and, to avoid processing delays, should preferably accompany the issue fee. Such submissions should be clearly labeled “Comments on Statement of Reasons for Allowance.”
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any extension fee pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner
should be directed to Matthew Ho whose telephone number is (571) 272-1388. The examiner can
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Navid Z Mehdizadeh can be reached on (571)-272-7691. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/MATTHEW HO/ Examiner, Art Unit 3669
/NAVID Z. MEHDIZADEH/ Supervisory Patent Examiner, Art Unit 3669
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