HERE Global B.V.

Patent Trials and Appeals Board

Dec 20, 2021

2020003277 (P.T.A.B. Dec. 20, 2021)

UNITED STATES PATENT AND TRADEMARK OFFICE
UNITED STATES DEPARTMENT OF COMMERCE
United States Patent and Trademark Office
Address: COMMISSIONER FOR PATENTS
P.O. Box 1450
Alexandria, Virginia 22313-1450
www.uspto.gov
APPLICATION NO. FILING DATE FIRST NAMED INVENTOR ATTORNEY DOCKET NO. CONFIRMATION NO.
14/821,040 08/07/2015 Xin Chen 10171-12027D
(NC58242US)
2664
101535 7590 12/20/2021
Lempia Summerfield Katz LLC/HERE
20 South Clark Street
Suite 600
Chicago, IL 60603
EXAMINER
AN, SHAWN S
ART UNIT PAPER NUMBER
2483
NOTIFICATION DATE DELIVERY MODE
12/20/2021 ELECTRONIC
Please find below and/or attached an Office communication concerning this application or proceeding.
The time period for reply, if any, is set in the attached communication.
Notice of the Office communication was sent electronically on above-indicated "Notification Date" to the
following e-mail address(es):
docket-us@lsk-iplaw.com
hereipr@here.com
pair_lsk@firsttofile.com
PTOL-90A (Rev. 04/07)
UNITED STATES PATENT AND TRADEMARK OFFICE
_______________

BEFORE THE PATENT TRIAL AND APPEAL BOARD
_______________

Ex parte XIN CHEN
_______________

Appeal 2020-003277
Application 14/821,040
Technology Center 2400
_______________

Before JEREMY J. CURCURI, NATHAN A. ENGELS, and
JAMES W. DEJMEK, Administrative Patent Judges.

DEJMEK, Administrative Patent Judge.

DECISION ON APPEAL
Appellant appeals under 35 U.S.C. § 134(a) from a Final Rejection of
claims 20–27 and 29–40.1 Appellant has canceled claims 1–19 and 28. See
Appeal Br. 27, 30. We have jurisdiction over the remaining pending claims
under 35 U.S.C. § 6(b).
We affirm.

1 Throughout this Decision, we use the word “Appellant” to refer to
“applicant” as defined in 37 C.F.R. § 1.42 (2019). Appellant identifies Here
Global B.V. as the real party in interest. Appeal Br. 2.
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STATEMENT OF THE CASE
Introduction
Appellant’s disclosed and claimed invention generally relates to
detecting common geographic features, such as road signs, text patterns in
road signs or road markings, in images to develop a navigation database.
Spec. 1:14–15, 3:5–7, 4:12–17, 9:3–11. In a disclosed approach, images are
processed to determine invariant components of the images or objects
therein. Spec. 5:25–30. “Invariant components or features are points,
gradients, vectors, and/or other components of objects or portions thereof in
an image that are invariant to scale, rotation, illumination or brightness of
the objects or portions thereof.” Spec. 9:16–18. The determined invariant
components are compared to reference components in a data library to
identify a particular geographic feature. Spec. 5:30–6:2.
Claim 20 is representative of the subject matter on appeal and is
reproduced below with the disputed limitations emphasized in italics:
20. An apparatus comprising:
at least one processor; and
at least one non-transitory computer readable memory
including computer program code for one or more programs; the
at least one non-transitory computer readable memory and the
computer program code configured to, with the at least one
processor, cause the apparatus to at least perform:
identifying an image of a path;
performing a comparison of an amplitude of a selected
pixel of the image to amplitudes of neighboring pixels;
determining an amplitude extremum for the image of the
path including the selected pixel based on the comparison;
identifying a standard path sign from the image based on
the amplitude extremum;
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determining data components that correspond to the
standard path sign based on the amplitude extremum, the data
components being scale-invariant components representing a
pattern of the standard path sign;
storing the data components that correspond to the
standard path sign in a navigation library of a map database
developer;
selecting another path sign image representing another
path;
determining scale-invariant components of the other path
sign image; and
comparing at least one extremum point of the determined
scale-invariant components of the other path sign image with at
least one amplitude extremum of the data components stored in
the navigation library to determine if the other path sign image
matches the standard path sign at a same angle or rotated at an
in-plane angle.

The Examiner’s Rejections2
1. Claims 20–23, 26, 27, 29, 32–36, 39, and 40 stand rejected
under pre-AIA 35 U.S.C. § 103(a) as being unpatentable over Zavoli et al.
(US 2009/0228204 A1; Sept. 10, 2009) (“Zavoli”); Culp et al. (US
6,937,747 B2; Aug. 30, 2005) (“Culp”); and Lowe (US 6,711,293 B1;
Mar. 23, 2004). Final Act. 4–9.
2. Claims 24, 30, and 37 stand rejected under pre-AIA 35 U.S.C.
§ 103(a) as being unpatentable over Zavoli, Culp, Lowe, and Silverbrook et
al. (US 6,720,985 B1; Apr. 13, 2004) (“Silverbrook”). Final Act. 4, 8.

2 In addition to the Final Rejection, the Examiner also refers to the body of
the rejections set forth in previous Non-Final Rejections (mailed
December 13, 2018 and January 12, 2018). See, e.g., Final Act. 4.
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3. Claims 24, 25, 30, 31, 37, and 38 stand rejected under pre-AIA
35 U.S.C. § 103(a) as being unpatentable over Zavoli, Culp, Lowe, and
Chen (US 8,441,489 B2; May 14, 2013). Final Act. 4, 8–9.

ANALYSIS3
Claims 20–26
Appellant asserts the cited prior art fails to teach, inter alia,
“identifying a standard path sign from the image based on the amplitude
extremum,” as recited in claim 20. Appeal Br. 8; Reply Br. 2. Further,
Appellant asserts that the Examiner does not rely on Zavoli to teach
identifying the standard path sign from the image based on the amplitude
extremum and that neither Culp nor Lowe teaches a standard path sign.
Appeal Br. 8.
The Examiner’s rejection is based on the combined teachings of
Zavoli, Culp, and Lowe. See Final Act. 4; see also 01/12/2018 Non-Final
Act. 3–5 (mailed January 12, 2018).4 More particularly, the Examiner finds
Zavoli teaches identifying a standard path sign from an image and relies on
Lowe’s teaching of, inter alia, determining an amplitude extremum for the
image. See 01/12/2018 Non-Final Act. 3–5 (citing Zavoli ¶ 67, Lowe,
col. 1, ll. 47–67, col. 2, ll. 1–3, col. 6, ll. 12–25, 58–67, col. 7, ll. 41–57,

3 Throughout this Decision, we have considered the Appeal Brief, filed
October 21, 2019 (“Appeal Br.”); the Reply Brief, filed March 27, 2020
(“Reply Br.”); the Examiner’s Answer, mailed January 28, 2020 (“Ans.”);
and the Final Office Action, mailed June 21, 2019 (“Final Act.”), from
which this Appeal is taken.
4 For clarity, we refer to the Non-Final Rejection mailed on January 12, 2018
as “01/12/2018 Non-Final Act.”
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col. 10, ll. 21–29, Figs. 6, 8, 9); see also Ans. 12–14. The Examiner reasons
that it would have been obvious to one of ordinary skill in the art to modify
Zavoli’s identification of a standard path sign from an image to incorporate
Lowe’s teaching determining an amplitude extremum for an image to allow
for identification of a standard path sign from an image “taken from any
direction and under varying light conditions.” 01/12/2018 Non-Final Act. 5.
As an initial matter, non-obviousness cannot be established by
attacking references individually where, as here, the ground of
unpatentability is based upon the teachings of a combination of references.
In re Keller, 642 F.2d 413, 426 (CCPA 1981). Rather, the test for
obviousness is whether the combination of references, taken as a whole,
would have suggested the patentee’s invention to a person having ordinary
skill in the art. In re Merck & Co., 800 F.2d 1091, 1097 (Fed. Cir. 1986).
Moreover, we find the Examiner’s findings are supported by a
preponderance of the evidence. In particular, Zavoli generally relates to map
matching using sensor-detected objects. See Zavoli, Abstract. More
specifically, Zavoli teaches that a camera (i.e., a sensor) positioned in a
vehicle may capture real-time images as the vehicle is moving. Zavoli ¶ 16.
From these captured images, objects such as a stop sign (i.e., a path sign)
may be identified. Zavoli ¶ 16; see also Zavoli ¶¶ 29 (describing an object
matching technique to disambiguate objects that a driver passes), 42
(describing identifying objects such as roadway signs). Further, contrary to
Appellant’s assertions (see, e.g., Reply Br. 2), we find Zavoli describes
extracting objects, such as a road sign, from sensor data (e.g., from a
camera). See Zavoli ¶ 67. Zavoli describes that raw sensor data is
processed, objects are extracted, and object characterization matching logic
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is used “to match the extracted objects with known objects.” Zavoli ¶ 78.
Thus, we find Zavoli teaches identifying a standard path sign from a
captured image.
In addition, Lowe generally relates to “identifying scale invariant
features in an image and . . . using such scale invariant features to locate an
object in an image.” Lowe, Abstract. Lowe teaches an approach for
identifying scale invariant features in an image by producing a plurality of
difference images by blurring an initial image and subtracting a blurred
image from the initial image to produce a difference image. Lowe, col. 1,
ll. 47–55. Lowe further teaches locating pixel amplitude extrema in the
difference images by comparing the amplitude of a pixel with that of its
neighboring pixels. Lowe, col. 1, ll. 60–67. In addition, Lowe teaches
producing a pixel gradient vector for each pixel in a difference image and
“using the pixel gradient vectors of pixels near an extremum to produce an
image change tendency vector having an orientation . . . associated with
respective maximal and minimal amplitude pixels in each difference image.”
Lowe, col. 2, ll. 4–10.
Further, Lowe describes that the magnitudes of pixel gradient vectors
within predefined orientation ranges may be accumulated and used to
describe scale invariant features of the image. See Lowe, col. 2, ll. 17–25.
Lowe also describes:
scale invariant features of the image under consideration are
correlated with scale invariant features of reference images
depicting known objects and detection of an object is indicated
when a sufficient number of scale invariant features of the image
under consideration define an aggregate correlation exceeding a
threshold correlation with scale invariant features associated
with the object.
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Lowe, col. 2, ll. 32–39.
Thus, using Lowe’s technique for identifying an object using scale
invariant features in combination with Zavoli’s system for capturing and
identifying road signs (e.g., a stop sign) from an image teaches “identifying
a standard path sign from the image based on the amplitude extremum,” as
recited in claim 20.
Appellant further asserts that the cited prior art fails to teach
“determining data components that correspond to the standard path sign
based on the amplitude extremum, the data components being scale-
invariant components representing a pattern of the standard path sign,” as
recited in claim 20. Appeal Br. 9. Appellant again argues that Zavoli does
not explicitly disclose the recited limitation and that “because Lowe does not
teach a standard path sign,” Lowe also fails to teach the recited limitation.
Appeal Br. 9.
Appellant’s argument is not persuasive of Examiner error because, at
least, it is not responsive to the rejection as articulated by the Examiner. As
discussed above, the Examiner relies on the combined teachings of Zavoli
and Lowe (as well as Culp) in rejecting claim 20. See 01/12/2018 Non-Final
Act. 3–5; Ans. 13–14. Moreover, as discussed above, Lowe teaches
determining data components that correspond to a reference object based on
the amplitude extremum (see, e.g., Lowe, col. 2, ll. 32–39) and Zavoli
teaches identifying a standard path sign from an image (see, e.g., Zavoli
¶¶ 16, 29, 42, 67, 78). Thus, we agree with the Examiner that Lowe’s
technique of determining the recited data components as applied to the
standard path sign of Zavoli teaches “determining data components that
correspond to the standard path sign based on the amplitude extremum, the
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data components being scale-invariant components representing a pattern of
the standard path sign,” as recited in claim 20.
Appellant also argues the cited prior art fails to teach storing the data
components that correspond to the standard path sign in a navigation library
of a map database. Appeal Br. 10–11; Reply Br. 2. More particularly,
Appellant argues “Zavoli is silent on the information being stored including
data components that are scale-invariant components representing a pattern
of the standard path sign.” Appeal Br. 10. Appellant further argues “Lowe
is silent, however, on the scale-invariant features corresponding to a
standard path sign.” Appeal Br. 11.
For similar reasons to those discussed above, we do not find
Appellant’s arguments responsive to the combined teachings of the
references. Moreover, as the Examiner explains, Zavoli teaches storing
object information in a digital map database. See Ans. 14 (citing Zavoli
¶¶ 37, 43, 63); see also Zavoli ¶ 36. Thus, we determine that Zavoli, as
modified by the teachings of Lowe, teaches storing the data components that
correspond to the standard path sign in a navigation library of a map
database, wherein the data components being scale-invariant components
representing a pattern of the standard path sign.
Accordingly, Appellant’s arguments are not persuasive of Examiner
error.
Appellant also asserts the cited prior art fails to teach “comparing at
least one extremum point of the determined scale-invariant components of
the other path sign image with at least one amplitude extremum of the data
components stored in the navigation library to determine if the other path
sign image matches the standard path sign at a same angle or rotated at an
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in-plane angle,” as recited in claim 20. Appeal Br. 11–13; Reply Br. 2–3. In
particular, Appellant argues “Lowe uses the scale invariant features to
determine an angle of the object within the image (e.g. from the viewpoint at
which the object was imaged), but is silent on determining the angle or
orientation of the object relative to the stored feature descriptors.” Appeal
Br. 12–13.
Lowe describes producing “a library of scale invariant features of
reference objects.” Lowe, col. 2, ll. 17–25. Further, Lowe describes
correlating scale invariant features of an image under consideration with the
scale invariant features of the reference images. Lowe, col. 10, ll. 13–16;
see also Lowe, col. 10, ll. 56–61 (describing matching scale invariant
features of the image under consideration to those from the reference
library). Lowe teaches the correlating technique involves determining
correlations between component subregion descriptors for a plurality of
subregions of pixels about pixel amplitude extrema for the image under
consideration and a reference image. Lowe, col. 10, ll. 21–29. Still further,
Lowe describes a process to determine the matching process, which
determines “the location of the object, the size of the object relative to the
scale of the image of the scale invariant feature from the library, the
orientation of the object, and an error residual value or degree of
correlation.” Lowe, col. 11, ll. 19–23 (emphasis added); see also Ans. 15–
16.
Based on our review of Lowe, we find Lowe (in combinations with
Zavoli’s teaching of identifying a standard path sign, discussed above)
teaches “comparing at least one extremum point of the determined scale-
invariant components of the other path sign image with at least one
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amplitude extremum of the data components stored in the navigation library
to determine if the other path sign image matches the standard path sign at a
same angle or rotated at an in-plane angle,” as recited in claim 20.
For the reasons discussed supra, we are unpersuaded of Examiner
error. Accordingly, we sustain the Examiner’s rejection of independent
claim 20. In addition, we sustain the Examiner’s rejections of claims 21–26,
which depend therefrom and were not argued separately. See Appeal Br. 13;
see also 37 C.F.R. § 41.37(c)(1)(iv).

Claims 27, 29–32
For the limitations of independent claim 27 that are commensurate in
scope to those of independent claims 20, Appellant advances similar
arguments to those presented regarding the rejection of claim 20. See
Appeal Br. 13–18.
For similar reasons to those discussed above with respect to
independent claim 20, Appellant’s arguments are not persuasive of
Examiner error.
In addition, Appellant argues the cited prior art fails to teach
“generating a modification for an attribute of the path in a navigational
database based on the comparison,” as recited in claim 27. Appeal Br. 18–
19. More particularly, Appellant argues Zavoli teaches updating a position
for a vehicle rather than a path attribute. Appeal Br. 18–19.
We do not find Zavoli is limited to only updating a position of a
vehicle, but instead also teaches determining and updating an attribute of
objects (which may include roadway objects related to the path) in a
navigational database. See, e.g., Zavoli ¶¶ 38, 41–42, 60, 77–78, 111. For
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example, as described in claim 1 of Zavoli, Zavoli recites comparing
information of a sensed object to that of an object extracted from the
database and “effecting . . . an adjustment of the positional information for
the extracted object as appearing in the database.” In other words, Zavoli
teaches determining and modifying an attribute of a reference object stored
in the navigational database based on a comparison to information from a
detected object.
For the reasons discussed supra, we are unpersuaded of Examiner
error. Accordingly, we sustain the Examiner’s rejection of independent
claim 27. In addition, we sustain the Examiner’s rejections of claims 29–32,
which depend therefrom and were not argued separately. See Appeal Br. 19;
see also 37 C.F.R. § 41.37(c)(1)(iv).

Claims 33–40
For the limitations of independent claim 33 that are commensurate in
scope to those of independent claims 20, Appellant advances similar
arguments to those presented regarding the rejection of claim 20. See
Appeal Br. 19–25. For the limitation of independent claim 33 that is
commensurate in scope to that of independent claims 27 (i.e., determining an
attribute of a road based on the comparison), Appellant advances similar
arguments to those presented regarding the rejection of claim 27.
For similar reasons to those discussed above with respect to
independent claims 20 and 27, Appellant’s arguments are not persuasive of
Examiner error.
Accordingly, we sustain the Examiner’s rejection of independent
claim 33. In addition, we sustain the Examiner’s rejections of claims 34–40,
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which depend therefrom and were not argued separately. See Appeal Br. 25;
see also 37 C.F.R. § 41.37(c)(1)(iv).

CONCLUSION
We affirm the Examiner’s decision rejecting claims 20–27 and 29–40
under pre-AIA 35 U.S.C. § 103(a).

DECISION SUMMARY
Claim(s)
Rejected
35 U.S.C. § Reference(s)/Basis Affirmed Reversed
20–23, 26,
27, 29, 32–
36, 39, 40
103(a) Zavoli, Culp, Lowe 20–23, 26,
27, 29, 32–
36, 39, 40

24, 30, 37 103(a) Zavoli, Culp, Lowe,
Silverbrook
24, 30, 37
24, 25, 30,
31, 37, 38
103(a) Zavoli, Culp, Lowe,
Chen
24, 25, 30,
31, 37, 38

Overall
Outcome
20–27, 29–
40

TIME PERIOD FOR RESPONSE
No time period for taking any subsequent action in connection with
this appeal may be extended under 37 C.F.R. § 1.136(a)(1)(iv). See
37 C.F.R. § 41.50(f).

AFFIRMED