Uniloc 2017 LLC

Patent Trials and Appeals Board

Jul 13, 2020

IPR2020-00170 (P.T.A.B. Jul. 13, 2020)

Trials@uspto.gov Paper 14
571-272-7822 Date: July 13, 2020

UNITED STATES PATENT AND TRADEMARK OFFICE

BEFORE THE PATENT TRIAL AND APPEAL BOARD

GOOGLE LLC,
Petitioner,
v.
UNILOC 2017 LLC,
Patent Owner.

IPR2020-00170
Patent 6,253,201 B1

Before BRYAN F. MOORE, LYNNE E. PETTIGREW, and
JON M. JURGOVAN, Administrative Patent Judges.
PETTIGREW, Administrative Patent Judge.
DECISION
Denying Institution of Inter Partes Review
35 U.S.C. § 314
I. INTRODUCTION
Petitioner, Google LLC, filed a Petition for inter partes review of
claims 1–14 and 17–20 of U.S. Patent No. 6,253,201 B1 (Ex. 1001, “the
’201 patent”). Paper 1 (“Pet.”). Patent Owner, Uniloc 2017 LLC, filed a
Preliminary Response. Paper 7 (“Prelim. Resp.”). Pursuant to our
authorization for supplemental briefing on the issue of discretionary denial
IPR2020-00170
Patent 6,253,201 B1
2
under 35 U.S.C. § 314(a), Petitioner filed a Reply to Patent Owner’s
Preliminary Response, and Patent Owner filed a Sur-reply. Paper 9 (“Pet.
Reply”); Paper 12 (“PO Sur-reply”); see Paper 8, 3 (authorizing reply and
sur-reply).
Under 35 U.S.C. § 314 and 37 C.F.R. § 42.4(a), we have authority to
institute an inter partes review if “the information presented in the
petition . . . and any response . . . shows that there is a reasonable likelihood
that the petitioner would prevail with respect to at least 1 of the claims
challenged in the petition.” 35 U.S.C. § 314(a). After considering the
parties’ briefing and the evidence of record, we conclude the information
presented does not show there is a reasonable likelihood that Petitioner
would prevail in establishing the unpatentability of at least one of claims 1–
14 and 17–20 of the ’201 patent. Accordingly, we do not institute an inter
partes review.
II. BACKGROUND
A. Related Matters
The parties identify the following district court proceeding related to
the ’201 patent: Uniloc 2017, LLC v. Google LLC, No. 2:18-cv-00548 (E.D.
Tex., filed Dec. 30, 2018). Pet. 3; Paper 3, 2 (Patent Owner’s Mandatory
Notices). That case has been transferred to the Northern District of
California. See Ex. 3002 (Transfer Order, June 19, 2020).
B. Overview of the ’201 Patent
The ’201 patent describes a system and method for matching a target
image to images stored in a database. Ex. 1001, 1:5–8. The disclosed
method determines similarity between images based on a count of the
number of corresponding partitions in each image having similar
characteristics. Id. at 2:38–42. For efficiency purposes, indexed lists of
IPR2020-00170
Patent 6,253,201 B1
3
image identifiers are maintained, and the count of similar characterizations
of an image is determined by the count of occurrences of the image’s
identifier in selected lists. Id. at 2:42–46. The selected lists are determined
by a characterization of a target image from which similar images are to be
identified. Id. at 2:46–48. The ’201 patent states that its indexing and
retrieval techniques are suitable for a variety of image characterization
techniques, such as those based on color content or edge content of partitions
of an image. Id. at 2:48–52.
Figure 1 of the ’201 patent is reproduced below:

Figure 1 above illustrates a block diagram of an image retrieval system
disclosed in the ’201 patent. Id. at 2:53–54. The image retrieval system
IPR2020-00170
Patent 6,253,201 B1
4
includes characterizer 120, which produces indices 102 and 112 to lists of
image identifiers 130, and search engine 140, which processes selected lists
of image identifiers 135 to determine images 181 that have a high number of
occurrences 161 in selected lists 135. Id. at 2:54–59.
A user provides a graphic representation of target image 101 to the
image retrieval system to determine images 111 of reference database 110
that are similar in characteristics to target image 101. Id. at 2:60–63.
Source 100 providing target image 101 may be, for example, an input device
such as an image scanner, a digitizer, or a camera. Id. at 2:63–65.
Reference image database 110 contains images that may be created and
stored using similar input devices. Id. at 3:5–9.
Each image 111 in reference image database 110 is provided to
characterizer 120 to create indexed lists of image identifiers 130. Id. at
IPR2020-00170
Patent 6,253,201 B1
5
3:24–26. Figure 2 of the ’201 patent, reproduced below, illustrates an
example block diagram of characterizer 120:

Id. at 3:26–29. As shown in Figure 2 above, characterizer 120 partitions
image 201 into an array of partitions (P) using partitioner 210. Id. at 3:31–
33. Characteristic processor 220 processes each image partition P to
produce characteristic measure 221 that describes the partition. Id. at 3:36–
39. Characteristic measure 221 may be, for example, a histogram of the
number of occurrences of particular colors or particular types of edges.
Id. at 3:39–44. Quantizer 230 quantizes characteristic measure 221 to
produce indexed characterizations (Idx). Id. at 3:48–51. For example,
IPR2020-00170
Patent 6,253,201 B1
6
quantizer 230 may place the characteristic measure into bins such as
quartiles (e.g., 0–25%, 26–50%, 51–75%, or 76–100% blue). Id. at 3:51–56;
see Pet. 13. Characterizer 120 outputs index 202, which includes the
identification P of each partition and the indexed characterization Idx.
Ex. 1001, 3:26–29, 4:10–11, 4:23–25.
Partition and characterization information in index 202 is arranged
into lists to facilitate searching. Id. at 4:10–5:3. Each image has
identifier 215 identifying the image (e.g., by location). Id. at 4:10–22. To
arrange the information into lists, the system stores identifier 215 of the
image in each list associated with a partition P of the image that has an
indexed characterization Idx. Id. at 4:23–25. For example, as shown in
Figure 2, if partition P1 corresponds to the upper left corner of each image,
and index I1 corresponds to an occurrence of predominantly red and blue
colors, list 135a will be a list of the identifiers (A, D, Q, R, K) of all
images 111 in database 110 that have predominantly red and blue colors in
the upper left corner. Id. at 4:25–31. Similarly, list 135b is a list of
identifiers (D, L) of images that have predominantly red and blue colors in
partition P2 (e.g., the lower left corner). Id. at 4:31–34.
Once the system characterizes and indexes the database images,
search engine 140 identifies reference images from the database similar to a
target image, which undergoes the same characterization process as the
reference database images. Id. at 2:53–59, 5:26–32, Fig. 1. The similarity is
determined by counting the number of occurrences of each reference
image 111 that has a corresponding partition with the same characteristics as
target image 101. Id. at 5:28–32, Fig. 4. To count the occurrences, the
system processes in a loop through the reference image database for each
indexed characterization and maintains a running count of how many times
IPR2020-00170
Patent 6,253,201 B1
7
an image identifier appears. Id. at 5:66–6:33, Fig. 4. The image identifier
with the highest count is identified as the closest match to target image 101.
Id. at 6:34–43.
C. Illustrative Claims
Challenged claims 1, 5, and 10 are independent. Claims 2–4 depend
directly from claim 1, claims 6–9 depend directly or indirectly from claim 5,
and claims 11–14 and 17–20 depend directly or indirectly from claim 10.
Claims 1 and 5 are illustrative of the claimed subject matter and are
reproduced below:
1. A method of image retrieval, comprising the steps of:
partitioning a target image into a plurality of content-
independent partitions,
characterizing each partition of the plurality of content-
independent partitions to form an index value associated with
each partition,
obtaining a list of image identifiers associated with the index
value,
accumulating counts of each image identifier in the list of
image identifiers associated with each partition of the plurality
of content-independent partitions, and
retrieving at least one image associated with at least one of the
image identifiers, based upon the counts of the at least one of
the image identifiers.
5. A method of indexing an image, comprising the steps of:
identifying the image by an image identifier,
partitioning the image into a plurality of content independent
partitions,
characterizing each content independent partition of the
plurality of partitions to form at least one index value of a
plurality of index values, and
appending the image identifier to at least one list of a plurality
of lists of image identifiers associated with each partition, the at
IPR2020-00170
Patent 6,253,201 B1
8
least one list being determined by the at least one index value
that characterizes the each partition.
Ex. 1001, 8:2–16, 8:29–42.
D. Asserted Ground of Unpatentability
Petitioner asserts that the challenged claims are unpatentable based on
the following ground (Pet. 7):
Claims Challenged 35 U.S.C. § References
1–14, 17–20 103(a)1 Hull,2 Barber3
In support of its contentions, Petitioner relies on the Declaration of
Dr. John R. Grindon (Ex. 1003).
III. ANALYSIS
A. Principles of Law
A claim is unpatentable under § 103(a) if the differences between the
claimed subject matter and the prior art are such that the subject matter, as a
whole, would have been obvious at the time the invention was made to a
person having ordinary skill in the art to which said subject matter pertains.
KSR Int’l Co. v. Teleflex Inc., 550 U.S. 398, 406 (2007). The question of
obviousness is resolved on the basis of underlying factual determinations,
including (1) the scope and content of the prior art; (2) any differences
between the claimed subject matter and the prior art; (3) the level of ordinary

1 The Leahy-Smith America Invents Act (“AIA”), Pub. L. No. 112-29, 125
Stat. 284, 285–88 (2011), revised 35 U.S.C. § 103 effective March 16, 2013.
Because the ’201 patent has an effective filing date prior to the effective date
of the applicable AIA amendment, we refer to the pre-AIA version of § 103.
2 U.S. Patent No. 5,465,353, issued Nov. 7, 1995 (Ex. 1005).
3 U.S. Patent No. 5,579,471, issued Nov. 26, 1996 (Ex. 1006).
IPR2020-00170
Patent 6,253,201 B1
9
skill in the art; and (4) when in evidence, objective indicia of
non-obviousness.4 Graham v. John Deere Co., 383 U.S. 1, 17–18 (1966).
An invention “composed of several elements is not proved obvious
merely by demonstrating that each of its elements was, independently,
known in the prior art.” KSR, 550 U.S. at 418. In an obviousness analysis,
“it can be important to identify a reason that would have prompted a person
of ordinary skill in the relevant field to combine the elements in the way the
claimed new invention does.” Id. Further, “[t]o satisfy its burden of proving
obviousness, a petitioner cannot employ mere conclusory statements. The
petitioner must instead articulate specific reasoning, based on evidence of
record, to support the legal conclusion of obviousness.” In re Magnum Oil
Tools Int’l, Ltd., 829 F.3d 1364, 1380 (Fed. Cir. 2016).
B. Level of Ordinary Skill in the Art
Petitioner asserts that a person of ordinary skill in the art at the time of
the alleged invention of the ’201 patent would have had “a bachelor’s degree
in electrical engineering, computer science, or computer engineering and had
two years of relevant experience, or a graduate degree with a focus, in the
field of image processing.” Pet. 18 (citing Ex. 1003 ¶¶ 52–53). Patent
Owner does not offer a proposal regarding the level of ordinary skill in the
art. Prelim. Resp. 24.
On the present record, we determine that Petitioner’s proposed level
of ordinary skill in the art is consistent with the ’201 patent and asserted
prior art. See Okajima v. Bourdeau, 261 F.3d 1350, 1355 (Fed. Cir. 2001).

4 With respect to the fourth Graham factor, the parties do not present
arguments or evidence regarding objective indicia of non-obviousness.
Therefore, the obviousness analysis at this stage of the proceeding is based
on the first three Graham factors.
IPR2020-00170
Patent 6,253,201 B1
10
Therefore, we adopt Petitioner’s proposal for purposes of deciding whether
to institute inter partes review.
C. Claim Construction
In an inter partes review, we apply the same claim construction
standard that would be used in a civil action under 35 U.S.C. § 282(b),
following the standard articulated in Phillips v. AWH Corp., 415 F.3d 1303
(Fed. Cir. 2005) (en banc). 37 C.F.R. § 42.100(b). In applying this
standard, we generally give claim terms their ordinary and customary
meaning, as would be understood by a person of ordinary skill in the art, at
the time of the invention and in the context of the entire patent disclosure.
Phillips, 415 F.3d at 1312–13.
Neither party proposes a construction for any claim term. Petitioner
contends that no claim terms require express construction for purposes of
applying the prior art. Pet. 19. Patent Owner argues that, at this stage of the
proceeding, the Board should adopt the ordinary and customary meaning of
the claim terms. Prelim. Resp. 25. For purposes of this decision, we
determine that no claim terms require express construction. See Nidec
Motor Corp. v. Zhongshan Broad Ocean Motor Co., 868 F.3d 1013, 1017
(Fed. Cir. 2017) (holding that only claim terms in controversy need to be
construed, and only to the extent necessary to resolve the controversy (citing
Vivid Techs., Inc. v. Am. Sci. & Eng’g, Inc., 200 F.3d 795, 803 (Fed. Cir.
1999))).
D. Asserted Obviousness over Hull and Barber
Petitioner contends that claims 1–14 and 17–20 of the ’201 patent are
unpatentable under 35 U.S.C. § 103 as obvious over the combined teachings
of Hull and Barber. Pet. 19–81. For the reasons discussed below, we
conclude that Petitioner has not demonstrated a reasonable likelihood it
IPR2020-00170
Patent 6,253,201 B1
11
would prevail in showing that any of the challenged claims are unpatentable
on this asserted ground.
1. Overview of Hull
Hull discloses a document matching and retrieval system that matches
an input document against a database of documents. Ex. 1005, code (57),
1:6–9, 4:33–36. Documents are digitally represented, and the content of a
document may be “text, line art, photographic images, computer-generated
images, or other information, or combinations of these types of content.”
Id. at 1:10–11, 1:27–29. In addition to a document database, the system
includes a descriptor database, which lists descriptors derived from features
of documents. Id. at 4:36–38. An entry in the descriptor database represents
a descriptor and points to a list of all documents in the document database
that include the feature associated with the descriptor. Id. at 4:39–42. “The
descriptors are selected to be invariant to distortions caused by digitizing the
documents and are redundant to accommodate noise in the digitization of the
documents or differences in the input document and its match in the
document database.” Id. at 4:42–46; see id. at code (57).
IPR2020-00170
Patent 6,253,201 B1
12
Figure 1 of Hull is reproduced below:

Figure 1 above illustrates a block diagram of a document storage system in
which digital representations of documents are stored along with descriptor
cross-references. Id. at 5:54–57. Document storage system 100 stores a
digital representation of a document in document database 108 while the
digital representation is passed to feature extractor 110. Id. at 6:59–61.
Feature extractor 110, which is supplied with descriptor rules for
determining which features of a document are extracted and converted to
descriptors, produces descriptor elements from the document’s digital
representation. Id. at 6:54–57, 6:62–63. “The descriptors are preferably
invariant of translation, rotation, scaling, format font and subdivision, so that
a given descriptor which is extracted from a document would still be
extracted, even if the document is scanned in a different orientation, is
resized or otherwise distorted.” Id. at 6:63–7:1. Feature extractor 110
provides descriptors extracted from a document, along with a document tag
IPR2020-00170
Patent 6,253,201 B1
13
provided by document tag manager 112, to descriptor database 116 when
hash generator 114 is not in use. Id. at 6:45–50; see id. at 7:66–8:1
(describing operation “[i]f hash generator 114 is not used”).
Figure 5 of Hull, annotated by Petitioner, is reproduced below:

Pet. 10 (citing Ex. 1005, Fig. 5). Annotated Figure 5 above illustrates the
organization of descriptor database 116, showing each descriptor followed
by a linked list of document tags identifying each document in document
database 108 from which the descriptor is extracted and saved. Ex. 1005,
21:7–11.
IPR2020-00170
Patent 6,253,201 B1
14
Figure 2 of Hull is reproduced below:

Figure 2 above illustrates a block diagram of a query engine used to locate
stored documents that match in whole or in part with a query document.
Id. at 5:58–60. Query engine 200 accepts, for example, electronic
document 203 or paper document 202 scanned by scanner 204 and, using
descriptor database 116 and document database 108, outputs a match
document (e.g., paper representation 220 or electronic document 222). Id. at
7:15–20. To perform a query, the system inputs a document’s digital
representation to feature extractor 210, which, using the provided descriptor
rules, derives descriptors from the query input. Id. at 7:61–65. If hash
generator 214 is not used, feature extractor 210 outputs the derived
descriptors to document matcher 216, which retrieves records for each of the
descriptors from descriptor database 116. Id. at 7:66–8:10. Each retrieved
record includes a list of documents associated with that descriptor. Id. at
8:10–12. Document matcher 216 accumulates votes for documents by
counting one vote for each time a document’s tag appears on a list associated
IPR2020-00170
Patent 6,253,201 B1
15
with a descriptor. Id. at 8:17–21. Document retriever 218 retrieves the
document with the most votes as the output match, or alternatively retrieves
all documents with more than a threshold number of votes. Id. at 8:23–32.
Hull describes the selection of descriptor rules provided to the feature
extractors. Id. at 9:45–10:19. “The descriptors provide a distortion-
invariant representation for local features in an image, and therefore a
descriptor is an independent source of information.” Id. at 9:47–49. “The
use of distortion-invariant descriptors requires that the feature extraction
stage be specialized . . . and dependent on the type of content of the image.”
Id. at 9:57–60. For example, when documents contain images of text, word
length pattern (i.e., an ordered list of the lengths of consecutive words) is a
good descriptor because it is not a function of the rotation, translation, or
scale of a document. Id. at 9:60–64. Hull provides an example
implementation of the disclosed system using such a descriptor for text
images. Id. at 13:4–15:61.
Hull further explains that its system is also applicable to graphic
document images and images with combined text and graphics. Id. at
20:34–37. For such images, feature extractors 110 and 210 would include
the ability to locate and characterize graphic features. Id. at 10:37–40. In
one embodiment, for example, the feature extractor scans the document for
regions of high spatial frequency objects or sharp contrast edges, referred to
as “interesting points.” Id. at 20:40–43. “To be invariant through
translation, rotation and scaling, a descriptor could be used which describes
the angular relationship between three or more such interesting points.
Additional relationships between interesting points can be used to normalize
the descriptor so that it is also invariant of aspect ratio changes.” Id. at
20:46–51.
IPR2020-00170
Patent 6,253,201 B1
16
2. Overview of Barber
Barber discloses a system for retrieving images from a database in
response to queries based on image characteristics such as colors, textures,
shapes, and sizes. Ex. 1006, code (57), 1:13–15. In one embodiment, the
system presents an image query window together with one or more image
characteristic windows, each representing a particular predefined image
characteristic and including a set of one or more thumbnails (i.e., icons)
corresponding to various values of the image characteristic represented by
the characteristic window. Id. at 3:8–14. The thumbnails represent aspects
of the image such as color, texture, shape, and area, and may be dragged to
the image query window where they may be arranged into a desired spatial
orientation corresponding to the positioning of image features. Id. at 3:14–
19.
In a second embodiment, an image characteristic selection area
includes a color palette or wheel, and a cursor-based mechanism enables a
user to point at a color in the selection area, select the color by clicking, and
draw or paint with the selected color in the image query area. Id. at 3:51–56.
This embodiment finds images according to a user-specified pattern
consisting of image characteristics at specified positions. Id. at 12:40–42.
Each image in the database is stored as a pixel array that is “spatially
partitioned, such as into a rectangular grid, a radial grid providing finer
granularity in the center of the image, or any other quantization that fits the
image data and application.” Id. at 12:48–52. Then, for each image in the
image database, using the areas defined by partitioning in the previous step,
the system computes a set of image characteristics for each area. Id. at
12:64–67. Image characteristics can include measures such as image color,
texture, or edge content. Id. at 12:67–13:2. The system stores the image
IPR2020-00170
Patent 6,253,201 B1
17
characteristics in a database organized by image and spatial partition. Id. at
13:5–46. When a user specifies a query by drawing or painting features in
an image query window, the system computes a similarity score for each
image in the database, ranks the images by their scores, and returns the
images with the best scores. Id. at 13:48–14:67.
3. Proposed Combination of Hull and Barber
In its proposed combination of the teachings of Hull and Barber,
Petitioner generally relies on Hull’s document matching algorithm and
database arrangement and Barber’s image partitioning and characterization
technique. See Pet. 19–20. For example, with respect to independent
claim 1, Petitioner cites Hull for teaching a “method of image retrieval,” as
recited in the preamble. Id. at 29–30 (citing Ex. 1005, code (57), 1:18–28).
For the step of “partitioning a target image into a plurality of content-
independent partitions,” Petitioner asserts that Hull teaches matching an
input document (i.e., the claimed “target image”) against a database of
documents (e.g., images) and cites Barber’s spatial partitioning (e.g., into a
rectangular grid) for teaching partitioning an image into content-independent
partitions. Id. at 30–32 (citing Ex. 1005, code (57), 1:18–28; Ex. 1006,
12:48–62, Figs. 11A, 11B).
With respect to the next limitation of claim 1, “characterizing each
partition of the plurality of content-independent partitions to form an index
value associated with each partition,” Petitioner relies on a combination of
Barber and Hull. Id. at 33–44. First, Petitioner contends that Barber’s
disclosure of computing a set of image characteristics for each image in an
image database, using the areas defined by the partitioning, corresponds to
“characterizing each partition of the plurality of content-independent
partitions.” Id. at 33–35 (citing Ex. 1006, 12:63–67; Ex. 1003 ¶¶ 83–84).
IPR2020-00170
Patent 6,253,201 B1
18
For the claimed “index value,” Petitioner turns to Hull’s disclosure of a
database organized by feature descriptors, in contrast to Barber’s database
organized by images. Id. at 35–39 (citing, e.g., Ex. 1005, 21:23–35, Fig. 5;
Ex. 1003 ¶¶ 87, 89). Petitioner contends that a person of ordinary skill in the
art would have understood the descriptors of the input document in Hull to
be within the scope of the claimed “form[ing] an index value” because the
input document descriptors serve as an index to address or find database
documents with the same descriptors. Id. at 39 (citing Ex. 1005, Fig. 5;
Ex. 1003 ¶ 91). Further, Petitioner asserts that a person of ordinary skill in
the art would have understood Hull’s descriptors (corresponding to the
claimed “index value[s]”) to be “associated with each partition” in the
proposed combination of Hull and Barber. Id. (citing Ex. 1003 ¶ 92). That
is, Petitioner contends it would have been obvious to a skilled artisan to
include partition information as part of the database index along with the
descriptors in the combined system. Id. at 39–40 (citing Ex. 1003 ¶ 92).
Petitioner relies on Hull for teaching the remaining limitations of
claim 1. First, Petitioner contends that Hull “obtain[s] a list of image
identifiers associated with the index value” when Hull’s descriptor
database 116 returns document tags associated with a descriptor. Id. at 44
(citing Ex. 1005, 8:6–16, 8:60–64, 21:7–11). Next, Petitioner asserts that
Hull “accumulat[es] counts of each image identifier in the list of image
identifiers associated with each partition of the plurality of content-
independent partitions” when Hull’s document matcher 216 accumulates
votes for documents by counting one vote for each time a document’s tag
appears on a list associated with a descriptor (which in the combination with
Barber includes partition information). Id. at 45 (citing Ex. 1005, 8:17–22).
Finally, Petitioner asserts that Hull “retriev[es] at least one image associated
IPR2020-00170
Patent 6,253,201 B1
19
with at least one of the image identifiers, based upon the counts of the at
least one of the image identifiers” when Hull’s document retriever 218
retrieves the document with the most votes as the output match. Id. at 45–46
(citing, e.g., Ex. 1005, 7:56–60, 8:6–32).
We now turn to Petitioner’s reasoning for the proposed combination
of Hull and Barber. See Pet. 19–29. Citing the testimony of Dr. Grindon,
Petitioner contends it would have been obvious to a person of ordinary skill
in the art to implement Hull’s search algorithm and database arrangement
using known image characterization techniques and image similarity
measures like those of Barber. Id. at 19–20 (citing Ex. 1003 ¶¶ 57–75).
Petitioner begins with Hull, asserting that it discloses a matching and
retrieval system that is equally applicable to text document images and
non-text images (i.e., graphics or pictures). Id. at 20 (citing Ex. 1003 ¶ 59;
Ex. 1005, 20:34–45). Petitioner contends that for graphic images, Hull
“broadly explains that . . . feature extractors would need to ‘include the
ability to locate and characterize graphical features,’ and provides, ‘in a
specific embodiment,’ a single example where the feature extractor scans for
edges.” Id. (quoting Ex. 1005, 20:34–45) (citing Ex. 1003 ¶ 59). Based on
Hull’s “broad instruction that its matching method is applicable to graphical
images and may use other feature extractors, a person of ordinary skill in the
art would have been motivated to look to other known methods for detecting
the ‘locat[ion] and characteriz[ation] [of] graphic[al] features,’” such as
Barber’s methods, “which characterize color and location.” Id. (quoting
Ex. 1005, 20:38–39) (citing Ex. 1005, 20:34–61, 22:45–60; Ex. 1003 ¶ 60).
Thus, Petitioner argues Hull’s disclosure “provides an express teaching,
suggestion, and motivation to modify Hull to use image feature extractors
from the prior art, such as those disclosed in Barber, to extract features
IPR2020-00170
Patent 6,253,201 B1
20
suitable for characterizing, and locating those characterizations within,
graphical images.” Id. at 20–21 (citing Ex. 1003 ¶ 60).
Petitioner provides additional reasons a person of ordinary skill in the
art allegedly would have been motivated to use Barber’s feature extractor.
Id. at 22–24. For instance, Petitioner contends that Barber’s feature
extractor “specifically focuses on and accounts for the use of color in
characterizing images,” whereas “the single non-text example disclosed in
Hull teaches using spatial frequency components (e.g., edges), but is silent
on color.” Id. at 22 (citing Ex. 1006, 16:20–43; Ex. 1005, 20:37–61;
Ex. 1003 ¶ 62). Petitioner also argues that Barber’s image characterization
algorithm “simply characterizes content-independent partitions and would
likely be computationally easier than the single non-text descriptor example
provided in Hull, which is more computationally demanding, involving
characterization of areas as well as comparing characteristics to nearby
areas.” Id. at 23–24 (citing Ex. 1003 ¶ 64).
In its Preliminary Response, Patent Owner asserts that Petitioner has
failed to demonstrate that a person of ordinary skill in the art, considering
Hull and Barber as a whole, would have combined the references as
proposed. Prelim. Resp. 25–35. Among other things, Patent Owner argues
that the Petition fails to acknowledge an essential teaching of Hull—the use
of descriptors selected to be invariant to distortions caused by digitizing the
documents. Id. at 25–26. Patent Owner further argues that, in view of that
key feature, Barber’s spatial partitioning technique is incompatible with
Hull. Id. at 26. For the reasons discussed below, we agree with Patent
Owner that Petitioner has not explained adequately why a person of ordinary
skill in the art would have been motivated to combine the teachings of Hull
IPR2020-00170
Patent 6,253,201 B1
21
and Barber in the manner proposed by Petitioner to achieve the claimed
invention.
As Patent Owner correctly points out, the second sentence of Hull’s
Abstract states that descriptors are selected to be invariant to distortions
caused by digitizing the documents. Ex. 1005, code (57); see Prelim.
Resp. 26–27. Similarly, Hull states in its Summary of the Invention that
“descriptors are selected to be invariant to distortions caused by digitizing
the documents and are redundant to accommodate noise in the digitization of
the documents or differences in the input document and its match in the
document database.” Ex. 1005, 4:42–46; see Prelim. Resp. 27. The
Summary of the Invention also identifies one of the problems addressed by
invariant descriptors: “The descriptors are preferably invariant of
translation, rotation, scaling, format, font and subdivision, so that a given
descriptor which is extracted from a document would still be extracted, even
if the document is scanned in a different orientation, is resized or otherwise
distorted.” Ex. 1005, 6:63–7:1; see Prelim. Resp. 28–29.
The description of Hull’s preferred embodiment also emphasizes that
Hull’s descriptors are invariant to distortion such as would occur through
translation, rotation, or scaling. For example, the first sentence under the
heading “Selection of Descriptor Rules” reads: “The descriptors provide a
distortion-invariant representation for local features in an image, and
therefore a descriptor is an independent source of information.” Ex. 1005,
9:47–49; see Prelim. Resp. 29. Further, the first sentence of the following
paragraph under the same heading states that “[t]he use of distortion-
invariant descriptors requires that the feature extraction stage be specialized
for this requirement.” Ex. 1005, 9:57–50; see Prelim. Resp. 29. And the
section of the written description explaining that Hull’s system is applicable
IPR2020-00170
Patent 6,253,201 B1
22
to graphic images discloses a descriptor that is invariant through translation,
rotation, and scaling, i.e., one that describes the angular relationship between
three or more “interesting points” determined by scanning the image for
“regions of high spatial frequency objects or sharp contrast edges.”
Ex. 1005, 20:40–48; see Prelim. Resp. 30.
Based on Hull’s several discussions of descriptors that are invariant to
distortion, we determine that a person of ordinary skill in the art would have
considered the invariant nature of Hull’s descriptors to be a significant
feature of the disclosed system. The Petition refers to this feature only once,
asserting that “Hull primarily utilizes text descriptors that are invariant
through rotation and scaling,” but that Hull “does not require or limit itself
to descriptors that are invariant to translation, rotation and scaling
distortions.” Pet. 40 (citing Ex. 1005, 9:46–49, 6:63–7:1 (stating that Hull’s
descriptors are “preferably invariant of translation, rotation, scaling, format,
font and subdivision”), claim 2 (requiring invariance in a dependent claim)).
In asserting that invariance is not required, however, the Petition fails to
address Hull’s other passages suggesting invariance is an essential feature of
Hull’s descriptors.
The Petition also dismisses Hull’s disclosure of a feature extractor for
graphic images as a single example that “scans for edges.” Pet. 20 (citing
Ex. 1005, 20:34–45). This overlooks Hull’s disclosure of a descriptor based
on the angular relationship between “interesting points” identified by the
feature extractor. See Ex. 1005, 20:40–48. Thus, rather than provide an
“express teaching, suggestion, and motivation to modify Hull to use image
feature extractors from the prior art, such as those disclosed in Barber,” as
Petitioner contends, Hull describes a feature extractor and a descriptor that
IPR2020-00170
Patent 6,253,201 B1
23
are consistent with Hull’s teaching of descriptors invariant of translation,
rotation, and scaling. Pet. 20.
In view of Hull’s emphasis on descriptors selected to be invariant to
distortions caused by digitizing documents, and Hull’s disclosure of a
distortion-invariant descriptor for documents containing graphic images,
Petitioner does not explain sufficiently why a person of ordinary skill in the
art would have modified Hull by replacing its feature extractor and
descriptor with Barber’s partitioning and characterizing process. See
TriVascular, Inc. v. Samuels, 812 F.3d 1056, 1066 (Fed. Cir. 2016) (holding
that an obviousness determination cannot be reached when the record lacks
“explanation as to how or why the references would be combined to produce
the claimed invention”). This is particularly true because, as Patent Owner
contends, Barber’s technique for spatial partitioning and characterization
based on measures such as image color, texture, and edge content appears to
be inconsistent with Hull’s teaching of descriptors that are invariant of
translation and rotation. See Prelim. Resp. 26. And although Petitioner
further contends that a person of ordinary skill in the art would have been
motivated to use Barber’s feature extractor with Hull’s matching process
when “comparison of color information is needed” or “speed/computation is
a concern” (Pet. 24), on the present record these arguments do not overcome
the Petition’s failure to consider Hull as a whole, including its teaching of
distortion-invariant descriptors as a key feature. See Polaris Indus., Inc. v.
Arctic Cat, Inc., 882 F.3d 1056, 1069 (Fed. Cir. 2018) (“[A reference’s]
statements regarding preferences are relevant to a finding regarding whether
a skilled artisan would be motivated to combine that reference with another
reference.”).
IPR2020-00170
Patent 6,253,201 B1
24
For at least these reasons, based on the record before us, we determine
that Petitioner has not adequately shown that a person of ordinary skill in the
art would have combined the teachings of Hull and Barber in the manner
asserted to achieve the claimed invention. Therefore, we conclude the
information presented does not demonstrate a reasonable likelihood that
Petitioner would prevail in establishing that claims 1–14 and 17–20 of the
’201 patent are unpatentable under 35 U.S.C. § 103(a) for obviousness over
the combination of Hull and Barber.
E. Discretionary Denial
Patent Owner argues that we should exercise our discretion under
35 U.S.C. § 314(a) to deny institution of inter partes review in this case in
view of the overlap between the Petition and district court litigation
involving the same parties. Prelim. Resp. 10–20; Sur-reply 1–7; see Pet.
Reply 1–7 (Petitioner addressing Patent Owner’s § 314(a) discretionary
denial arguments). Patent Owner also argues that we should exercise our
discretion under 35 U.S.C. § 325(d) to deny institution of inter partes
review. Prelim. Resp. 20–23. Because we have considered the merits of the
Petition and decline to institute an inter partes review on that basis, we need
not determine whether it would be appropriate to deny the Petition pursuant
to our discretion under § 314(a) or § 325(d).
IV. CONCLUSION
After considering the parties’ evidence and arguments, we determine
that the information presented does not show a reasonable likelihood that
Petitioner would prevail in establishing that at least one of claims 1–14 and
17–20 of the ’201 patent is unpatentable on the ground asserted in the
Petition.
IPR2020-00170
Patent 6,253,201 B1
25
V. ORDER
Accordingly, it is
ORDERED that the Petition is denied, and no inter partes review is
instituted.

PETITIONER:

Erika H. Arner
Daniel C. Cooley
A. Grace Mills
FINNEGAN, HENDERSON, FARABOW, GARRETT & DUNNER LLP
erika.arner@finnegan.com
daniel.cooley@finnegan.com
gracie.mills@finnegan.com

PATENT OWNER:

Ryan Loveless
Brett Mangrum
James Etheridge
Brian Koide
Jeffrey Huang
ETHERIDGE LAW GROUP
ryan@etheridgelaw.com
brett@etheridgelaw.com
jim@etheridgelaw.com
brian@etheridgelaw.com
jeff@etheridgelaw.com