TRW Automotive U.S. LLCv.Magna Electronics Inc.

Patent Trial and Appeal Board

Jun 25, 2015

12273879 (P.T.A.B. Jun. 25, 2015)

Trials@uspto.gov Paper 37
Tel: 571-272-7822 Entered: June 25, 2015

UNITED STATES PATENT AND TRADEMARK OFFICE
_______________
BEFORE THE PATENT TRIAL AND APPEAL BOARD
_______________
TRW AUTOMOTIVE US LLC,
Petitioner,
v.
MAGNA ELECTRONICS INC.,
Patent Owner.
_______________

Case IPR2014-00262
Patent 7,655,894 B2
_______________

Before JUSTIN T. ARBES, BENJAMIN D. M. WOOD, and
NEIL T. POWELL, Administrative Patent Judges.

WOOD, Administrative Patent Judge.

FINAL WRITTEN DECISION
35 U.S.C. § 318(a) and 37 C.F.R. § 42.73

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I. INTRODUCTION
A. Background
TRW Automotive US LLC (“TRW”) filed a Petition (Paper 1, “Pet.”)
to institute an inter partes review of claims 1–5, 9, 10, 12–21, and 24–28 of
U.S. Patent No. 7,655,894 B2 (Ex. 1002, “the ’894 patent”). Magna
Electronics Inc. (“Magna”) filed a Preliminary Response. Paper 7. We
instituted an inter partes review of claims 1–3, 5, 10, 13–16, 25, 26, and 28
based on the following proposed grounds of unpatentability:
Reference[s] Basis Claims Challenged
Yanagawa,1 Vellacott,2 and
Koshizawa3 § 103(a) 1–3, 5, and 10
Yanagawa, Vellacott, Koshizawa,
and Bottesch4 § 103(a) 16
Yanagawa, Vellacott, Koshizawa,
and Aurora5 § 103(a) 13 and 14
Yanagawa, Vellacott, Koshizawa,
and Kawahara6 § 103(a) 15, 25, 26, and 28

After the Board instituted trial, Magna filed a Patent Owner Response
(Paper 23, “PO Resp.”), to which TRW replied (Paper 27, “Pet. Reply”).

1 JP S62-131837 to Yanagawa (June 15, 1987) (Ex. 1005).
2 Oliver Vellacott, CMOS in Camera, IEE REVIEW (May 1994) (Ex. 1007).
3 US 5,177,606 to Koshizawa (Jan. 5, 1993) (Ex. 1008).
4 US 5,166,681 to Bottesch et al. (Nov. 24, 1992) (Ex. 1010).
5 Mai Chen, AURORA: A Vision-Based Roadway Departure Warning
System, 1995 IEEE/RSJ INT’L CONG. ON INTELLIGENT ROBOTS AND SYS.
(Aug. 9, 1995) (Ex. 1012).
6 US 4,758,883 to Kawahara (Jul. 19, 1988) (Ex. 1013).
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Oral Hearing was held on February 19, 2015, and the Hearing Transcript
(Paper 36, “Tr.”) has been entered in the record.
We have jurisdiction under 35 U.S.C. § 6(c). This Final Decision is
entered pursuant to 35 U.S.C. § 318(a). We determine that TRW has not
shown by a preponderance of the evidence that the challenged claims are
unpatentable.
B. Related Proceedings
TRW discloses that the ’894 patent has been asserted in Magna
Electronics, Inc. v. TRW Automotive Holdings Corp., Case No. 1:12-cv-
00654-PLM (W.D. Mich. 2012). Pet. 6.
C. The ’894 Patent (Ex. 1002)
The ’894 patent, titled “Vehicular Image Sensing System,” describes a
system for controlling a vehicle—e.g., dimming the vehicle’s headlights—
in response to detecting “objects of interest” in front of the vehicle—e.g., the
headlights of oncoming vehicles and the taillights of leading vehicles.
Ex. 1002, 1:19–24. The system uses an image sensor that divides the scene
in front of the vehicle into “a plurality of spatially separated sensing
regions.” Id. at 2:9–12. A control circuit with a processor receives image
data from the image sensor and determines if individual regions include light
sources having a particular characteristic, such as a “spectral characteristic”
(color), or intensity. Id. at 1:60–66, 5:48–56. By comparing the lights’
characteristics with the “distribution” of the lights across the spatially
separated sensing regions, such as the lights’ proximity to each other and to
the vehicle’s central axis, the system can distinguish oncoming headlights
and leading taillights from streetlights and other lights that are not of interest
to the system. Id. at 2:38–49.
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D. Illustrative Claims
Of the claims at issue in this proceeding, claims 1 and 25 are
independent, and each is drawn to an image sensing system for a vehicle.
Ex. 1002, 12:18–15:37. Claims 2, 3, 5, 10, and 13–16 depend directly or
indirectly from claim 1, and claims 26 and 28 depend directly or indirectly
from claim 25. Id. at12:18–16:9.
The independent claims share at least three common limitations:
(1) an imaging sensor comprising a two-dimensional array of light-sensing
photosensor elements; (2) the imaging sensor being inside the vehicle on
which it is mounted, having a forward field of view through the vehicle’s
windshield; and (3) a logic and control circuit comprising a processor that
processes the image data to identify objects of interest. Ex. 1002, 12:18–32,
13:55–67, 14: 31–42, 15:11–24. Independent claim 1 is illustrative and is
reproduced below:
1. An image sensing system for a vehicle, said image sensing
system comprising:
an imaging sensor comprising a two-dimensional array of
light sensing photosensor elements formed on a semiconductor
substrate;
wherein said imaging sensor is disposed at an interior
portion of the vehicle proximate the windshield of the vehicle
and wherein said interior portion is at or proximate to an
interior rearview mirror assembly of the vehicle and wherein
said imaging sensor has a forward field of view to the exterior
of the vehicle through the windshield;
a logic and control circuit comprising an image processor
for processing image data derived from said imaging sensor;
wherein said image sensing system identifies objects of
interest by processing said image data to identify objects of
interest based at least on spectral differentiation; and
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wherein identification of objects of interest is enhanced by
comparing over successive frames image data associated with
objects in said forward field of view of said image sensor.

II. ANALYSIS
A. Claim Construction
“A claim in an unexpired patent shall be given its broadest reasonable
construction in light of the specification of the patent in which it appears.”
37 C.F.R. § 42.100(b); see In re Cuozzo Speed Tech., LLC, 778 F.3d 1271,
1281 (Fed. Cir. 2015) (“We conclude that Congress implicitly adopted the
broadest reasonable interpretation standard in enacting the AIA.”). Under
that standard, the claim language should be read in light of the specification
as it would be interpreted by one of ordinary skill in the art. In re Suitco
Surface, Inc., 603 F.3d 1255, 1260 (Fed. Cir. 2010). Thus, we generally
give claim terms their ordinary and customary meaning. See In re
Translogic Tech., Inc., 504 F.3d 1249, 1257 (Fed. Cir. 2007) (“The ordinary
and customary meaning is the meaning that the term would have to a person
of ordinary skill in the art in question.”) (internal quotation marks omitted).
We construe the following term in claim 1: “wherein identification of
objects of interest is enhanced by comparing over successive frames image
data associated with objects in said forward field of view of said image
sensor” (“the enhanced limitation”). No other terms require express
construction for purposes of this decision.

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“wherein identification of objects of interest is enhanced by
comparing over successive frames image data associated with
objects in said forward field of view of said image sensor”

The parties dispute the meaning of this term, and in particular the
meaning of the phrase “the identification of objects of interest is enhanced.”
Magna argues that this phrase means “the quality of the identification of
objects [of interest] is improved.” PO Resp. 6. According to Magna,
The ordinary and customary meaning of the term “enhanced” is
“to increase or improve in value, quality, desirability, or
attractiveness.” (Merriam-Webster definition of “enhance,”
Ex. 2034). The phrase “is enhanced” directly follows
“identification of objects of interest.” Accordingly, the plain
language of claim 1 is clear that the quality of the identification
of objects is improved.
Id. Magna asserts that the ’894 patent Specification “is consistent with this
construction,” as it explains that “using a plurality of frames [of image data]
guards against erroneous object detection due to noise and eliminates
headlamp toggling when sources are at the fringe of the detection range.”
Id. at 6–7 (quoting Ex. 1002, 7:28–37). Thus, Magna asserts that “the
recited enhancement is part of the object-identification process, not separate
from it.” Id. at 7.
TRW’s position, however, is that the construction of “identification of
objects of interest is enhanced” in claim 1 “includes identifying a further
characteristic of an object of interest.” Pet. Reply 3. Like Magna, TRW
finds support for its proposed interpretation in the dictionary definition of
“enhanced” set forth in Ex. 2034. Id. at 2; see Tr. 8:23–9:14 (agreeing with
Magna that “enhanced” means “to increase or improve value [or] the quality,
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desirability or attractiveness”). And, again like Magna, TRW finds support
for its proposed construction in the Specification. TRW states:
[T]he ’894 Patent describes (i) obtaining information on object
motion, (ii) by comparing objects over successive frames,
(iii) to enhance object recognition. While the ’894 Patent does
use hysteresis, it is clear that the ’894 Patent also initially
identifies a headlight or taillight spectral signature in a single
frame. See 1002 at 6:32–7:17. The hysteresis is used to
determine when to send a signal to switch the headbeam state,
not to identify an object. See 1002 at 7:28–35.
Id. at 2–3 (emphasis in original).
The claim language at issue recites that the “identification of objects
of interest is enhanced” (emphasis added). It does not, as TRW’s arguments
suggest, recite that the knowledge of various aspects of the object of interest
is enhanced. Further, using the definition of “enhance” on which the parties
apparently agree (PO Resp. 6 (quoting Ex. 2034); Pet. Reply 2 (same)), the
plain meaning of “identification of objects of interest is enhanced” is that the
identification of objects of interest is improved, e.g., in quality, as Magna
proposes. That is, the quality of the identification of objects of interest is
better than it would have been if the identification had not been based on
processing multiple frames of image data.
The Specification supports this interpretation in two ways. First, the
Specification uses the term “enhance” in the context of describing
processing techniques that improve the quality of an identification of an
object of interest—i.e., that improve the likelihood of correctly identifying,
or “recognizing,” objects of interest, and ignoring objects not of interest.
For example, the Specification teaches that
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The present invention is capable of utilizing spatial filtering to
even further enhance the ability to identify light sources. . . .
For example, it can be concluded that very closely adjacent red
and white light sources are not of interest as oncoming
headlights or taillights . . . [because they] can be identified as a
streetlight.
Ex. 1002, 10:18–31 (emphasis added). Likewise, the Specification teaches
that
Pattern recognition may be used to further assist in the
detection of headlights, taillights, and other objects of interest.
. . . By looking for a triad pattern, including the center high-
mounted stoplight required on the rear of vehicles, stoplight
recognition can be enhanced. Furthermore, “object recognition
can be enhanced by comparing identified objects over
successive frames. This temporal processing can yield
information on object motion and can be used to assist in
qualifying or disqualifying objects of interest.
Id. at 10:33–45.
Second, the Specification teaches that processing image data over
several frames does, in fact, improve the quality of the identification of
objects of interest. In particular, the Specification teaches a control routine
that “requir[es] that a headlight spectral signature or a taillight spectral
signature [to] be detected for a number of frames prior to switching the
headlights to a low-beam state.” Id. at 7:28–31. Doing so “guards against
erroneous detection due to noise in a given frame.” Id. at 7:33–36. That is,
this control routine improves the quality of the identification of objects of
interest by reducing the chance that noise in a single frame will cause the
system to erroneously detect an object of interest when none is present.
We do not find persuasive TRW’s argument that Magna’s
interpretation “reads out embodiments where an object of interest is
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recognized in a single frame.” Pet. Reply 2. The interpretation does not
require that the identification of objects of interest always requires
processing of multiple frames of image data; rather, it means that an
identification based on processing multiple frames of image data is less
likely to be erroneous than an identification based on the processing of a
single frame of image data. To summarize, we agree with Magna that the
broadest reasonable interpretation of “identification of objects of interest is
enhanced” is that the quality of the identification of objects of interest is
improved. Further, the quality of such identification is improved when the
possibility of error is reduced.7
B. Claims 1–3, 5, and 10—Obviousness—Yanagawa, Vellacott,
and Koshizawa
A claim is unpatentable under 35 U.S.C. § 103 if the differences
between the subject matter sought to be patented 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 the
subject matter pertains. KSR Int’l Co. v. Teleflex, Inc., 550 U.S. 398, 406
(2007). In the Decision to Institute, we adopted Petitioner’s proposed
definition of a person having ordinary skill in the art of the ’894 patent at the
time of the invention, which was supported by Dr. Miller’s testimony.

7 We note that our construction is consistent with the court’s construction of
the same term in Magna Elec., Inc. v. TRW Automotive Holdings Corp., Civ.
No. 1:12-cv-654, slip op. at 22 (W.D. Mich. Apr. 28, 2015p ). There, the
court adopted Magna’s construction of the term, i.e., that “identification of
objects if interest is improved.” Id. The court explained that “the
specification and claims describe a system that operates better after
comparing successive frames than it would if it captured only one frame.”
Id. at 23.
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Dec. 12–13. The parties have not disputed this definition, and we see no
reason to modify it in light of the record developed during trial. Therefore,
we conclude that a person of ordinary skill in the art would have had at least
the qualifications of or equivalent to either (1) a master’s degree in electrical
engineering or computer science, with course work or research in vision
systems, or (2) an undergraduate degree in electrical engineering or
computer science with at least two years of work making optical vision
systems. Id. (citing Pet. 22, Ex. 1014 ¶ 19).
1. Claim 1
TRW relies on Yanagawa as teaching most of the limitations of
independent claim 1. Pet. 21–22. Yanagawa describes a vehicle-mounted
imaging apparatus that detects the high beams of oncoming vehicles and
taillights of leading vehicles based on the “color features” of the lights and
whether the lights are at the same height. Ex. 1005, 002–003. Yanagawa’s
system dims the vehicle’s headlights in response to such detection. Id. at
001.
TRW relies on the following excerpt from Yanagawa to teach the
enhanced limitation:
The distance between vehicles is calculated in this way every
0.05 second as the image data are stored, and the speed of the
device vehicle relative to a vehicle traveling ahead is calculated
from the distance between vehicles obtained every 0.05 second.
Specifically, 0.05 second after a taillight image such as shown
in Fig. 5(A) has been obtained, the same taillight image is
shown in Fig. 5(B), and the distance between taillights 52 and
53 changes from r1 to r2.
Pet. 27 (quoting Ex. 1005, 4).
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Magna responds that TRW is “[u]sing an incorrect construction of
‘identification of objects of interest is enhanced’” to support its
unpatentability argument. PO Resp. 9. Magna asserts that the quoted
passage explains how Yanagawa’s system calculates the distance between
the equipped vehicle and a vehicle traveling ahead, and the relative speed of
the vehicle traveling ahead, but does not describe identifying objects of
interest or enhancing such identification. Id. at 9–10. According to Magna,
the described distance and speed calculations are unrelated to and separate
from the step of recognizing headlights and taillights in Yanagawa, and, in
fact, are carried out after Yanagawa’s system already has recognized the
leading vehicle’s taillights. Id. at 10 (citing Ex. 1005, Fig. 3).
TRW does not dispute that the portion of Yanagawa on which it relies
to teach this limitation does not involve the actual identification of objects of
interest. Instead, TRW argues that this portion “expressly determines at
least two further characteristics of identified taillights and vehicles thereof,”
i.e. speed of the vehicle and distance to the device vehicle. Pet. Reply 3
(emphasis omitted). Further, TRW argues that Yanagawa teaches this
limitation even under Magna’s interpretation, because “Yanagawa utilizes
speed and distance calculation . . . to enhance identification of objects by
identifying detected objects as potential rear-end collision objects.” Id. at 4.
As an initial matter, there is no dispute that the portion of Yanagawa
on which TRW relies teaches “comparing over successive frames image data
associated with objects in said forward field of view of said image sensor.”
Further, there does not seem to be any dispute that the portion of Yanagawa
on which TRW relies describes calculating the relative speed and distance of
an object of interest that has already been identified as such. Therefore, the
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dispute is whether that teaching corresponds to “enhanc[ing]” “identification
of objects of interest” as claim 1 requires. We determine that it does not. As
discussed above, we construe “identification of objects of interest is
enhanced” to mean that the quality of the identification of objects of interest
is improved; i.e., that the identification is less likely to be erroneous. But, as
Magna correctly points out, Yanagawa’s speed and distance calculations of a
leading vehicle are independent of its identification of the leading vehicle as
an object of interest; nor does Yanagawa teach that such calculations reduce
the possibility of error in an identification of an object of interest. See PO
Resp. 9–10; Ex. 2032 ¶¶ 27–36 (supporting testimony of Matthew A. Turk,
Ph.D.).
In its Reply, TRW argues that even under Magna’s construction,
Yanagawa teaches the “enhanced” limitation. Pet. Reply 4. According to
TRW, “Yanagawa utilizes speed and distance calculation . . . to enhance
identification of objects by identifying detected objects as potential rear-end
collision objects.” Id. TRW refers to Yanagawa’s teaching that “because
the distance between vehicles and relative speed have been calculated in this
case, these data can be used to predict a potential rear-end collision.” Id.
(quoting Ex. 1005, 005) (emphasis omitted).
As an initial matter, this argument is newly raised in the Reply, and is
based on a portion of Yanagawa that TRW alleges, for the first time,
corresponds to the enhanced limitation. Although the argument is based on
Magna’s proposed claim construction rather than the construction that TRW
proposes in its Reply,8 we consider the dispute over the proper construction

8 TRW did not propose a construction for the enhanced limitation in the
Petition.
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of this term to be sufficiently foreseeable so that TRW should have
presented the argument and evidence in the Petition. TRW’s failure to do so
at that time has deprived Magna of the opportunity to respond to it, as
Magna could not respond to TRW’s Reply. For this reason, we decline to
consider it. See Office Patent Trial Practice Guide, 77 Fed. Reg. 48,756,
48,767 (Aug. 14, 2012) (stating that a reply that belatedly presents evidence
will not be considered, and that one indication that a new issue has been
raised in a reply is where the petitioner submits “new evidence necessary to
make out a prima facie case” of unpatentability of an original claim).
Even if we were to consider this argument, however, we would find it
unpersuasive. TRW does not point us to anything in Yanagawa that
suggests that a previously identified vehicle becomes a new “collision
object” when it becomes a collision hazard. Nor do we find any such
teaching in the reference. Instead, the vehicle remains a known (i.e.,
identified) object regardless of its speed and distance relative to the equipped
vehicle.
In sum, we determine that TRW has not shown by a preponderance of
the evidence that claim 1 would have been obvious over Yanagawa,
Vellacott, and Koshizawa.
2. Claims 2, 3, 5, and 10
Claims 2, 3, 5, and 10 depend from claim 1, and, therefore,
necessarily contain the enhanced limitation. TRW relies on its discussion of
claim 1 with respect to this limitation in the dependent claims. Pet. 30–34.
Therefore, for the reasons set forth above, we determine that TRW has not
shown by a preponderance of the evidence that claims 2, 3, 5, and 10 would
have been obvious over Yanagawa, Vellacott, and Koshizawa.
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C. Claims 13–16—Obviousness—Yanagawa, Vellacott,
Koshizawa, and Bottesch (Claim 16), Aurora (Claims 13 and
14), or Kawahara (Claim 15)
Claims 13–16 depend from claim 1, and, therefore, necessarily
contain the enhanced limitation. TRW relies on its discussion of claim 1
with respect to this limitation in these dependent claims. Pet. 38, 40–44.
Therefore, for the reasons set forth above, we determine that TRW has not
shown by a preponderance of the evidence that claims 13–16 would have
been obvious over Yanagawa, Vellacott, Koshizawa, and Bottesch (claim
16), Aurora (claims 13 and 14), or Kawahara (claim 15).
D. Claims 25, 26, and 28—Obviousness—Yanagawa, Vellacott,
Koshizawa, and Kawahara
Claim 25 is independent. It does not contain the enhanced limitation,
but instead recites “wherein a comparison is made by said logic and control
circuit of a frame comprising image data to a successor frame in order to
identify, at least in part, an object of interest.” Claims 26 and 28 depend
from claim 25. TRW asserts that the following portion of Yanagawa teaches
this limitation:
The distance between vehicles is calculated in this way every
0.05 second as the image data are stored, and the speed of the
device vehicle relative to a vehicle traveling ahead is calculated
from the distance between vehicles obtained every 0.05 second.
Specifically, 0.05 second after a taillight image such as shown
in Fig. 5(A) has been obtained, the same taillight image is
shown in Fig. 5(B), and the distance between taillights 52 and
53 changes from r1 to r2.
Pet. 47, 50, 57 (quoting Ex. 1005, 004). This is the same passage on which
TRW relies in the Petition as teaching the enhanced limitation of claim 1.
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Magna disputes that this portion of Yanagawa teaches this limitation.
As it argued with respect to the enhanced limitation in claim 1, and based on
the same reasoning, Magna argues that this passage “is unrelated to the
identification of objects.” PO Resp. 21. TRW likewise counters with the
same arguments it raised with respect to claim 1. Pet. Reply 5.
Claim 25 expressly requires that the comparison of a frame of image
data with a successor frame be for the purpose of “identify[ing], at least in
part, an object of interest.” For the reasons discussed above in Section
II.B.1, we determine that the passage on which TRW relies is not directed to
the identification of objects of interest; instead, it describes calculating the
relative speed and distance of a previously identified object of interest.
Accordingly, for the reasons discuss above, we determine that TRW has not
shown by a preponderance of the evidence that claims 25, 26, and 28 would
have been obvious over Yanagawa, Vellacott, Koshizawa, and Kawahara.
III. CONCLUSION
For the foregoing reasons, we determine that TRW has not shown by
a preponderance of the evidence that claims 1–3, 5, 10, 13–16, 25, 26, and
28 of the ’894 patent are unpatentable under 35 U.S.C. § 103(a).
IV. ORDER
For the reasons given, it is
ORDERED that claims 1–3, 5, 10, 13–16, 25, 26, and 28 of the ’894
patent have not been shown to be unpatentable.

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This is a Final Decision. Parties to the proceeding seeking judicial
review of the decision must comply with the notice and service requirements
of 37 C.F.R. § 90.2.

PETITIONER:

Josh Snider
A. Justin Poplin
Timothy Sendek
LATHROP & GAGE LLP
patent@lathropgage.com
jpoplin@lathropgage.com
tsendek@lathropgage.com

PATENT OWNER:

David K.S. Cornwell
Jason Eisenberg
Robert Sterne
STERNE, KESSLER, GOLDSTEIN & FOX PLLC
Davidc-PTAB@skgf.com
jasone-PTAB@skgf.com
rsterne-PTAB@skgf.com

Timothy A. Flory
Terence J. Linn
GARDNER, LINN, BURKHART & FLORY, LLP
Flory@glbf.com
linn@glbf.com