TRW Automotive US LLCv.Magna Electronics Inc.

Patent Trials and Appeals Board

Jun 26, 2014

13204106 - (D) (P.T.A.B. Jun. 26, 2014)

Trials@uspto.gov Paper 15
Tel: 571-272-7822 Entered: June 26, 2014

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 IPR2014-00265
Patent 8,222,588 B2
_______________

Before JUSTIN T. ARBES, BARRY L. GROSSMAN, and
BEVERLY M. BUNTING, Administrative Patent Judges.

GROSSMAN, Administrative Patent Judge.

DECISION
Denying Institution of Inter Partes Review
37 C.F.R. § 42.108

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I. INTRODUCTION
TRW Automotive US LLC (“Petitioner”) filed a Petition requesting an inter
partes review of claims 28-38 of U.S. Patent No. 8,222,588 B2 (“the ’588 patent”).
Paper 1 (“Pet.”). The patent owner, Magna Electronics Inc. (“Patent Owner”),
filed a Preliminary Response. Paper 7 (“Prelim. Resp.”).
The standard for instituting an inter partes review is set forth in 35 U.S.C.
§ 314(a):
THRESHOLD – The Director may not authorize an inter partes
review to be instituted unless the Director determines that the
information presented in the petition filed under section 311 and any
response filed under section 313 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.
We determine that the information presented does not show that there is a
reasonable likelihood that Petitioner would prevail in establishing the
unpatentability of any of claims 28-38. Accordingly, we deny the Petition and do
not institute an inter partes review of the ’588 patent.
A. Related Proceedings
TRW states that the ’588 patent is involved in a pending district court case,
titled Magna Electronics Inc. v. TRW Automotive Holding Corp., No. 1:12-cv-
00654-PLM (W.D. Mich.). Pet. 4-5.
B. The ’588 Patent
The challenged claims are directed to an image sensing system. Ex. 1002,
col. 12, l. 58. The patent relates, in particular, to a system for controlling the
headlights of a vehicle. Id., col. 1, ll. 23–25. The disclosed system particularly is
adapted to controlling the vehicle’s headlamps in response to sensing the
headlights of oncoming vehicles and taillights of leading vehicles. Id., col. 1, 25–
28. The image processing system is capable of identifying unique characteristics
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of light sources by comparing light source characteristics with spectral signatures
of known light sources, such as headlights and taillights. Id., col. 1, l. 67–col. 2, l.
9.
As shown generally in Figure 2 of the ’588 patent, reproduced below, the
image processing system includes imaging sensor module 14, which senses light
from a scene forward of the vehicle; imaging control circuit 13
1
, which receives
data from sensor 14; and vehicle lighting control logic module 16, which
exchanges data with control circuit 13 and controls headlamps 18 for the purpose
of modifying the headlight beam. Ex. 1002, col. 3, ll. 44–51.

Fig. 2 of the ’588 patent.

1
The Specification also refers to imaging control circuit 13 as a “digital signal
processor.” See Ex. 1002, col. 3, l. 47 (“imaging control circuit 13”); col. 4, ll. 53–
54 (“digital signal processor 13”). This explains why reference numeral 13 in
Figure 2 points to a box labelled “DSP.”
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Imaging sensor module 14 includes a lens, an array of photon-accumulating
light sensors, and a spectral separation device, such as a filter array, for separating
light from the scene forward of the vehicle into a plurality of spectral bands. Ex.
1002, col. 4, ll. 24–29. Digital signal processor 13 includes an analog-to-digital
converter, which receives the output of the array of photon-accumulating light
sensors and converts the analog pixel values to digital values. Id. at col. 4, ll. 56–
58. The digital values are supplied to a taillight detection circuit and a headlight
detection circuit. Id. at col. 4, ll. 58–60.
The taillight detection circuit detects a red light source having intensity
above a particular threshold. Ex. 1002, col. 5, ll. 4–5. For each pixel that is “red,”
a comparison is made with adjacent “green” pixels and “blue” pixels. Id. at col. 5,
ll. 6–7. If the intensity of a red pixel is more than a particular number of times the
intensity of an adjacent green pixel and an adjacent blue pixel, then it is determined
that the light source is red. Id. at col. 5, ll. 7–10. The headlight detection circuit
carries out a similar process. Id. at col. 5, ll. 13–21. The image processing system
recognizes the spectral signatures of detected light sources, i.e., headlights and
taillights, as well as the spectral signatures of rejected light sources, such as lane
markers, signs, and other sources of reflected light, all of which may be readily
identified by their spectral signature. Id., col. 10, ll. 38–47.
C. Illustrative Claim
Challenged claims 28 and 35 are independent claims. Claim 35, reproduced
below, is illustrative of the claimed invention:
1. An image sensing system for a vehicle, said image
sensing system comprising:
an imaging sensor comprising a two-dimensional array of
light sensing pixels;
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said imaging sensor having a forward field of view through
the windshield of a vehicle equipped with said image sensing
system to the exterior of the equipped vehicle;
wherein said imaging sensor is operable to capture image
data;
a control comprising an image processor;
wherein said image sensing system determines an object of
interest present in said forward field of view of said imaging
sensor via processing of said captured image data by said image
processor;
wherein said image processing comprises spatial filtering;
wherein said spatial filtering enhances determination of at least
one of a headlamp of an approaching vehicle ahead of the
equipped vehicle and a taillight of a leading vehicle ahead of the
equipped vehicle; and
wherein said spatial filtering comprises analysis of a spectral
signature representative of at least one detected light source
present in said forward field of view of said imaging sensor.
D. References Relied Upon
Petitioner relies upon the following prior art references:

Reference Date Exhibit Number
Yanagawa,
Japanese Kokai
Application, No. S62-
131837, with certified
translation.
Published June 15, 1987 Ex. 1004
Kenue,
U.S. Pat. No. 4,970,653.

Issued Nov. 13, 1990 Ex. 1005
Tadashi,
Japanese Kokai
Application No. Hei 4-
127280, with certified
translation.
2

Published April 28, 1992 Ex. 1006

2
We refer to “Yanagawa” and “Tadashi” as the English translations of the original
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Vellacott,
“CMOS in Camera”, IEE
Review (May 1994).
May 1994 Ex. 1007
Venturello,
European Patent
Application Publication
No. 0 353 200.
Published Jan. 31, 1990 Ex. 1008
Bendell,
U.S. Pat. No. 4,521,804.
Issued June 4, 1985 Ex. 1010
E. The Asserted Grounds
Petitioner asserts the following grounds of unpatentability under 35 U.S.C.
§ 103:
Claims Challenged Statutory Basis References
28, 29, 30, 31, 32, 33,
and 34
103(a) Yanagawa
Kenue
Tadashi
Vellacott
Venturello
35, 37 and 38 103(a) Yanagawa
Kenue
Tadashi
Bendell
36 103(a) Yanagawa
Kenue
Tadashi
Bendell
Venturello
II. ANALYSIS
A. Claim Construction
In an inter partes review, “[a] claim in an unexpired patent shall be given its
broadest reasonable construction in light of the specification of the patent in which

references. Petitioner provided affidavits attesting to the accuracy of the
translations. See Exs. 1005, 1007; 37 C.F.R. § 42.63(b).
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it appears.” 37 C.F.R. § 42.100(b); see also Office Patent Trial Practice Guide, 77
Fed. Reg. 48,756, 48,764, 48,766 (Aug. 14, 2012) (Claim Construction); In re Am.
Acad. of Sci. Tech. Ctr., 367 F.3d 1359, 1364 (Fed. Cir. 2004). “[W]hen
interpreting a claim, words of the claim are generally given their ordinary and
accustomed meaning, unless it appears from the specification or the file history
that they were used differently by the inventor.” In re Paulsen, 30 F.3d 1475, 1480
(Fed. Cir. 1994). Any special definition for a claim term must be set forth in the
specification with reasonable clarity, deliberateness, and precision. Id. (citation
omitted). Against this background of general principles, we construe relevant
terms in the ’588 patent.
Petitioner proposes specific construction of the claim terms “spatial
filtering” (Pet. 7); “spectral,” “spectral characteristic,” or “spectral signature” (Pet.
9); and “pattern recognition” (Pet. 11). Patent Owner asserts specific constructions
for the phrase “spatial filtering” (Prelim. Resp. 29); and the phrase “said spatial
filtering identifies, at least in part, atmospheric conditions,” recited in claim 28
(Prelim. Resp. 30). For purposes of this decision, we conclude that only “spatial
filtering” needs to be interpreted.
“Spatial filtering”
Petitioner proposes that the claim term “spatial filtering” should be
construed to mean “categorization of data that involves an assessment of
information obtained from both a first pixel or group of pixels and a second pixel
or group of pixels, wherein the first pixel or group of pixels is adjacent or closely
related to the second pixel or group of pixels.” Pet. 9.
Patent Owner asserts that Petitioner misconstrued the phrase “spatial
filtering” (Prelim. Resp. 29) and that Petitioner’s proposed construction “is wrong
because it does not include a spectral signature component” (id. at 30).
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The Specification states that “[b]y spatial filtering is meant consideration of
not only whether a particular pixel, or pixel group, is detecting a light source
having a particular spectral signature, but also what adjacent, or closely related,
pixels or pixel groups, are detecting.” Ex. 1002, col. 10, ll. 55–59 (emphasis
added). We agree with Patent Owner that the Specification thereby expressly
defines the term “spatial filtering.” This definition is fully consistent with the
claims, which state the result of spatial filtering. For example, claim 30 states that
spatial filtering, at least in part, identifies atmospheric conditions by detecting the
effect on a light source caused by different types of atmospheric conditions; claim
33 states that spatial filtering enhances determination of a light source; and claim
35 states that spatial filtering enhances determination of a headlamp or a taillight.
Based on the evidence before us and for purposes of this Decision, the
broadest reasonable construction in light of the Specification of the claim term
“spatial filtering” is consideration of not only whether a particular pixel, or pixel
group, is detecting a light source having a particular spectral signature, but also
what adjacent, or closely related, pixels or pixel groups, are detecting.
E. Asserted Grounds of Unpatentability
1. Claims 28 and 35
Petitioner asserts that independent claims 28 and 35 would have been
obvious based on a combination of references, including Yanagawa, Kenue, and
Tadashi. Pet. 14, 41.
3

Claims 28 and 35 require that the image processing include “spatial
filtering” and, in claim 28, that the spatial filtering, at least in part, identify
atmospheric conditions. Petitioner relies on Yanagawa, Kenue, or Tadashi for the

3
We focus on these three references because analysis of these references is
dispositive of our Decision.
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disclosure of spatial filtering. For purposes of this Decision, we have construed the
phrase “spatial filtering” to mean “consideration of not only whether a particular
pixel, or pixel group, is detecting a light source having a particular spectral
signature, but also what adjacent, or closely related, pixels or pixel groups, are
detecting.” Spatial filtering, as defined, requires detection of a light source having
a particular spectral signature. The Specification of the ’588 patent states that
spectral characteristics are used in identifying a light source by comparing the
spectral characteristics with spectral signatures of known light sources, such as
those of headlights and taillights. Ex. 1002, col. 2, ll. 5–9. As explained in the
Specification, taillights are detected by identifying and analyzing a “red” pixel
from the visible light electromagnetic spectrum, whereas headlights are detected by
identifying and analyzing red, green, and blue pixels. Accordingly, a “spectral
signature” is a unique identifier of visible light based on wavelengths of the
electromagnetic spectrum. Spatial filtering, thus, requires detecting this unique
identifier of visible light.
The Specification states that spatial filtering can be useful in identifying
atmospheric conditions by detecting effects on light sources caused by particular
types of atmospheric conditions. Ex. 1002, col. 11, ll. 15–17. As explained in the
Specification, fog, or fine rain, tends to produce a dispersion effect around light
sources, which creates a series of transition regions surrounding the light source.
Id. at col. 11, ll. 20-22. By placing appropriate limits on the size of the transition
region, fog or light rain, or a mixture of both, or other related atmospheric
conditions, can be detected. Id. at col. 11, ll. 24–26.
Petitioner asserts that Yanagawa discloses an image sensing system using
“spatial filtering.” Pet. 19. According to Petitioner, Yanagawa recognizes
taillights “when two closely related pixels or pixel groups each indicate the
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presence of red light, and recognizes headlights when two closely related pixels or
pixel groups each indicate the presence of white luminescent colors. Id., citing Ex.
1004, 1004-003.
4
The cited disclosure in Yanagawa, however, does not refer to
pixels or pixel groups. The cited disclosure, which Petitioner quotes accurately,
states that recognition unit 143 determines whether the image, from which features
have been extracted, is a taillight based on whether there are two red images at the
same height. Ex. 1005, 1005-003.
Patent Owner asserts that Petitioner “failed to show how the applied
references suggest this requirement [spatial filtering] of the claims.” Prelim. Resp.
40-41.
Yanagawa discloses a recognition device for a traveling vehicle that
recognizes the presence of taillights of a vehicle traveling ahead and headlights of
an oncoming vehicle. Ex. 1005, 1005-001, col. 2. The recognition device uses an
imaging sensor, such as a color television camera. Id. at 1005-002, col. 2. The
device extracts color features of headlights and taillights to form a feature
extracted color image signal based on a color video signal imaged by the imaging
apparatus, recognizes the headlights and taillights of a vehicle ahead, and controls
the headlight beams based on this recognition result. Id. As shown in Figure 1
from Yanagawa, reproduced below, a video signal of images from television
camera 11 is supplied to decoder 13. Decoder 13 forms R (red), G (green) and B
(blue) color image signals based on the video signal, and supplies the color image
signals to image signal processor 14. Id. at 1005-003. Features are extracted by
image signal processor 14 from the color image signal, and the luminescent colors
of white and red are emphasized. Id. Image signal processor 14 includes features

4
The citation is to the unique, sequential page number of the exhibit. 37 C.F.R.
§ 42.63(d)(2)(i).
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extraction unit 141, as shown in Figure 4, reproduced below. Id. The R, G and B
color image signals from decoder 13 are supplied to features extraction unit 141,
where the inputted image signals “are binarized” to capture only information
relating to headlights and taillights. Id. Based on the information captured,
recognition unit 143 determines whether the image is a taillight. Id. Recognition
unit 143 makes this determination according to whether there are two red images at
the same height. Id.

Figure 1 from Yanagawa

Figure 4 from Yanagawa
Petitioner, however, has not pointed us to sufficient evidence showing that
Yanagawa discloses or suggests spatial filtering as required by claims 28 and 35,
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i.e., consideration of not only whether a particular pixel, or pixel group, is
detecting a light source having a particular spectral signature, but also what
adjacent, or closely related, pixels or pixel groups, are detecting. The disclosure on
which Petitioner relies, a determination based on the physical height of two
detected red lights, is a recognition of a pattern; it is not spatial filtering as required
by the claims of the ’588 patent.
5

Alternatively, Petitioner asserts that both Kenue and Tadashi disclose spatial
filtering. Pet. 21.
Petitioner asserts the boundary tracing algorithm of Kenue includes spatial
filtering, as claimed in claims 28 and 35. Pet. 20. Patent Owner’s declarant,
Jeffrey A. Miller, Ph.D., opines that Kenue “shows spatial filtering.” Ex. 1012, ¶
19, p. 1009-14.
Kenue discloses that the boundary tracing algorithm saves connected or
adjacent pixels, and follows the contour of a lane marker or a road edge in all
directions. Ex. 1005, col. 6, ll. 7–9. Next, obstacle detection is performed by
counting edge pixels within the lane boundaries and within 50 feet of the vehicle.
Id. at col. 6, ll. 18–20. We note that the Specification of the ’588 patent states that
“[l]ane markers, signs, and other sources of reflected light . . . may be readily
identified by spectral signature.” Ex. 1002, col. 10, ll. 45–47.
Kenue programs a computer with algorithms for processing the images
sensed by the camera. Ex. 1005, col. 2, ll. 40–41. Kenue discloses two main
algorithms for processing the image. One uses a Hough transform and the other
uses template matching. Id. at col. 2, ll. 41–44. In the template matching

5
See discussion of pattern recognition in the ’588 patent (Ex. 1002, col. 11, ll. 1–
14), which discusses the fact that headlights and taillights usually occur in pairs.
Pattern recognition is not spatial filtering (e.g., id. at col. 10, ll. 55–59).
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algorithm, a template or window of desired intensity and shape is correlated with
the image to create a correlation matrix. Id. at col. 3, ll. 22–26. In the Hough
algorithm, the intensity of pixels is determined and used to identify lane markers
and obstacles. Id. at col. 6, ll. 47–60. Thus, the algorithms in Kenue rely on
intensity or shape, not color, to identify objects of interest. Indeed, the system in
Kenue does not analyze color, because Kenue uses a “black and white CCD video
camera.” Id. at col. 2, ll. 29–30. Because Kenue does not detect color, Kenue does
not consider any “spectral signature” and, therefore, does not provide “spatial
filtering,” as required by claims 28 and 35.
As a second alternative, Petitioner asserts that Tadashi discloses spatial
filtering. Pet. 19. According to Petitioner, Tadashi uses spatial filtering to detect
the presence of tunnels. Id. Petitioner cites and quotes from the Tadashi
disclosure, which discusses detecting black level and white level regions of an
image. Id. Petitioner does not direct our attention to any disclosure in Tadashi that
provides “spatial filtering,” as required by claims 28 and 35. We are not persuaded
that Tadashi’s black and white image processing constitutes “spatial filtering” as
required by claims 28 and 35.
Petitioner also relies on the declaration of Dr. Miller. Dr. Miller essentially
repeats Petitioner’s assertions in opining that Yanagawa, Kenue, and Tadashi
disclose spatial filtering. Ex. 1009, ¶ 19, p. 1009-13–1009-15.
Based on the analysis above, we are not persuaded that Yanagawa, Kenue,
or Tadashi discloses spatial filtering as required by claims 28 and 35.
Moreover, Petitioner does not provide a persuasive explanation as to why a
person of ordinary skill would combine the technologies of Kenue or Tadashi with
Yanagawa to defeat patentability of claims 28 and 35. The rationale provided is
that the proposed modification “would merely be a use of known techniques to
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improve similar devices in the same way.” See Pet. 21. This “rationale” is a
restatement of one of the basic tests identified by the Supreme Court for
determining whether an invention would have been obvious. KSR, 550 U.S. 416
(“The combination of familiar elements according to known methods is likely to be
obvious when it does no more than yield predictable results.”) Restatement of
general principles on what may constitute a supporting rationale cannot substitute
for specific application of those principles to the facts. Petitioner does not provide
a persuasive fact-based analysis to support the proposed combination of references.
Further, Petitioner does not rely on the additional references asserted against
claims 28 and 35, that is, Vellacott, Venturello, and Bendell, as teaching the
“spatial filtering” recited in claim 1. Pet. 14–15, 23, 42.
Accordingly, based on the arguments and evidence of Petitioner, we are not
persuaded that there is a reasonable likelihood that Petitioner would prevail in
challenging the patentability of claims 28 and 35 or the claims dependent thereon,
which include claims 29–34 and 36–38. Petitioner has the burden of proof to
establish a reasonable likelihood of prevailing on its asserted grounds. Based on
what is presented in the Petition and supporting declaration, Petitioner has not met
that burden.
III. CONCLUSION
For the foregoing reasons, based on the information presented in the
Petition, we determine that Petitioner has not demonstrated a reasonable likelihood
that it would prevail in establishing that any of claims 28–38 of the ’588 patent are
unpatentable. Accordingly, we deny the Petition and do not institute an inter
partes review of claims 28–38 of the ’588 patent.
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IV. ORDER
For the reasons given, it is
ORDERED that the Petition challenging the patentability of claims 28–38 of
U.S. Patent No. 8,222,588 B2 is denied.

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FOR PETITIONER:

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

FOR PATENT OWNER:

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

David K.S. Cornwell
STERNE, KESSLER, GOLDSTEIN & FOX PLLC
davidc-PTAB@skgf.com