Ex Parte Zhang et al

Patent Trial and Appeal Board

Nov 30, 2016

13298615 (P.T.A.B. Nov. 30, 2016)

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.
13/298,615 11/17/2011 Wende Zhang P016924-RD-SDJ 6247
81466 7590 12/02/2016
MacMillan, Sobanski & Todd, LLC - GM
One Maritime Plaza
720 Water Street
5 th Floor
Toledo, OH 43604
EXAMINER
PARIKH, DAKSHESH D
ART UNIT PAPER NUMBER
2488
NOTIFICATION DATE DELIVERY MODE
12/02/2016 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):
docketing @ mstfirm.com
PTOL-90A (Rev. 04/07)
UNITED STATES PATENT AND TRADEMARK OFFICE
BEFORE THE PATENT TRIAL AND APPEAL BOARD
Ex parte WENDE ZHANG and JINSONG WANG
Appeal 2016-001767
Application 13/298,615
Technology Center 2400
Before CAROLYN D. THOMAS, ERIC B. CHEN, and
JOHN R. KENNY, Administrative Patent Judges.
CHEN, Administrative Patent Judge.
DECISION ON APPEAL
Appeal 2016-001767
Application 13/298,615
This is an appeal under 35 U.S.C. § 134(a) from the final rejection of
claims 1—20, all the claims pending in the application. We have jurisdiction
under 35 U.S.C. § 6(b). We affirm-in-part.
STATEMENT OF THE CASE
Appellants’ invention relates to distinguishing between daytime
lighting conditions and nighttime lighting conditions based on a captured
image by a vision-based imaging device along a path of travel. (Abstract.)
Claims 1,3, and 9 are exemplary, with disputed limitation in italics:
1. A method of distinguishing between daytime lighting
conditions and nighttime lighting conditions based on a captured
image by a vision-based imaging device along a path of travel, the
method comprising the steps of:
capturing an image by a vision-based imaging device;
selecting a region of interest in the captured image;
determining a light intensity value for each pixel within the
region of interest;
generating a cumulative histogram based on light intensity
values within the region of interest, the cumulative histogram
including a plurality of category bins representing the light intensity
values, each category bin identifying an aggregate value of light
intensity values assigned to each respective category bin;
comparing an aggregate value within a predetermined category
bin of the histogram to a first predetermined threshold', and
determining whether the image is captured during the daytime
lighting conditions as a function of the aggregate value within the
predetermined category bin.
3. The method of claim 2 wherein the determination of
whether the captured image is obtained during the daytime lighting
conditions further comprises the step of determining whether the
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captured image includes a daylight blocking structure over the path of
travel.
9. The method of claim 8 wherein determining that the
capture image is obtained during nighttime lighting conditions further
comprises the step of determining whether the nighttime lighting
conditions include substantial lighting for illumination the path of
travel in response to the aggregate value being greater than the first
predetermined threshold, wherein determining an illumination of the
path of travel comprises:
comparing an aggregate value of a second predetermined
category bin of the cumulative histogram to a third predetermined
threshold;
determining whether an aggregate value of the light intensity
values within the second predetermined category bin is less than the
third predetermined threshold; and
determining that the captured image includes the path of travel
in the captured image is substantially illuminated in response to the
second predetermined category being less than the third
predetermined threshold.
Claims 1—3 and 6 stand rejected under 35 U.S.C. § 102(b) as
anticipated by Zhu (US 2008/0069400 Al; Mar. 20, 2008).
Claims 4, 7—9, and 14—20 stand rejected under 35 U.S.C. § 103(a) as
unpatentable over Zhu.
Claim 5 stands rejected under 35 U.S.C. § 103(a) as unpatentable over
Zhu and Wildervanck (US 2008/0167810 Al; July 10, 2008).
Claims 10-13 stand rejected under 35 U.S.C. § 103(a) as unpatentable
over Zhu and Schofield (US 2003/0205661 Al; Nov. 6, 2003).
The Examiner has withdrawn the rejection of claim 1 under the
judicially created doctrine of obviousness-type double patenting as
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unpatentable over claims 20-23 of commonly owned Zhang (US 9,445,011
B2; Sept. 13,2016). (Ans. 3.)
§102 Rejection—Zhu
Claims 1 and 6
First, we are unpersuaded by Appellants’ arguments (App. Br. 8—9;
see also Reply Br. 2) that Zhu does not describe the limitation “generating a
cumulative histogram based on light intensity values within the region of
interest,” as recited in independent claim 1.
The Examiner found that the automatic context categorization of Zhu,
which selects the lower two-thirds of image pixels and clusters images with
similar histograms, corresponds to the limitation “generating a cumulative
histogram based on light intensity values within the region of interest.”
(Ans. 14—15; see also Final Act. 4—6.) We agree with the Examiner.
Zhu “relates to vision systems for vehicle detection that can adapt to
changing visibility conditions.” (12.) Figure 1 of Zhu illustrates a series of
images and related histograms captured in various lighting conditions (120)
with “[automatic context categorization of the input frames based on the
histogram of pixel intensities” (| 43). Zhu explains that “the lighting
context of an image will be defined from the histogram of its lower two-
thirds” (153) such that “[ijmage samples are first grouped into a number of
clusters, where images with similar histograms are categorized into a same
cluster” (| 55). Because Zhu explains that the lower two-thirds of an image
are used to generate the histogram and that such images are clustered by
similar histograms, Zhu discloses the limitation “generating a cumulative
histogram based on light intensity values within the region of interest.”
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Appellants argue that “[i]n Zhu, histograms 105-108, illustrated in
Fig. 1 of Zhu, show distributed histograms” and “[t]he Examiner relies on
Par [0043] to describe the cumulative histogram; however, Par [0043] or any
other section in Zhu fails to teach the cumulative histogram.” (App. Br. 8
(emphasis omitted).) In particular, Appellants argue that “[f]or the
cumulative histogram represented by Fig. 4 [of the Specification], the counts
of the all the bins leading up to a specified bin are added” and “each
respective bin in the cumulative histogram maintains a running total of all
the previous bins leading up to each specified bin, whereas distributive
histograms maintain the allocation of values to their assigned bins (i.e.,
counts are not additive as the graph progresses).” (Reply Br. 2.) However,
Appellants’ arguments are not commensurate in scope with claim 1, because
the claim does not require each respective bin in the cumulative histogram to
maintain a running total of all the previous bins leading up to each specified
bin. Appellants have not pointed to any special definition of “cumulative
histogram” from the Specification that would require a different
interpretation.
Therefore, we agree with the Examiner that Zhu describes the
limitation “generating a cumulative histogram based on light intensity values
within the region of interest.”
Second, we are unpersuaded by Appellants’ arguments (App. Br. 9;
see also Reply Br. 3) that Zhu does not describe the limitation “comparing
an aggregate value within a predetermined category bin of the histogram to a
first predetermined threshold,” as recited in independent claim 1.
The Examiner found that the identification of saturated images and
assigning such saturated images to a separate cluster corresponds to the
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limitation “comparing an aggregate value within a predetermined category
bin of the histogram to a first predetermined threshold.” (Ans. 15; see also
Final Act. 4—6.) We agree with the Examiner.
Zhu explains that “[f]or saturated images, majority of image pixels
assume values only in the lowest (from 0 to 9 for 8 bit image) and highest
bins (from 245 to 255 for 8 bit images) in their histograms” and “[i]t is
straightforward to identify saturated images from their histograms by
examining the percentage of pixels falling into the lowest and highest bins.”
(1 69.) Thus, because the saturated images of Zhu for the lowest or highest
bins (i.e., the claimed “a predetermined category bin”) would also produce
corresponding frequency values (i.e., the y-axis in a histogram) for such
bins, Zhu discloses the limitation “comparing an aggregate value within a
predetermined category bin of the histogram to a first predetermined
threshold.”
Appellants argue “Zhu describes identifying saturated images from
their histograms by examining the percentage of pixels falling into the
lowest and highest bins” and “[identifying the percentage of pixels falling
into the lowest and highest bins does not teach each category bin identifies
an aggregate value of light intensity values assigned to each respective
category bin.” (Reply Br. 3 (emphasis omitted); see also App. Br. 9.)
However, because Zhu explains that histograms having values only in the
lowest (from 0 to 9 for 8 bit image) and highest bins (from 245 to 255 for 8
bit images) are identified and such bins have corresponding frequency
values, Zhu discloses the limitation “comparing an aggregate value within a
predetermined category bin of the histogram to a first predetermined
threshold.”
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Therefore, we agree with the Examiner that Zhu describes the
limitation “comparing an aggregate value within a predetermined category
bin of the histogram to a first predetermined threshold.”
Third, we are unpersuaded by Appellants’ arguments (App. Br. 9—10)
that Zhu does not describe the limitation “determining whether the image is
captured during the daytime lighting conditions as a function of the
aggregate value within the predetermined category bin,” as recited in
independent claim 1.
The Examiner found that the four categories of Zhu, including Night,
Low Light (LL), Daylight (DL) and Saturation, correspond to the limitation
“determining whether the image is captured during the daytime lighting
conditions as a function of the aggregate value within the predetermined
category bin.” (Ans. 16; see also Final Act. 4—6.) We agree with the
Examiner.
Figure 3 of Zhu illustrates “the type of image and histogram
associated with a particular cluster of images” (1 69), including Night (| 70),
Low Light (LL) (| 71), Day Light (DL) (| 72), and Saturated (173).
Figure 3 also illustrates distinct histograms for Low Light (LL) and Day
Light (DL) conditions. Furthermore, Figure 1 of Zhu illustrates histogram
108 for daylight conditions, with pixel values ranging from about 150 to
about 180 (i.e., bins) with each pixel value corresponding to a specific
frequency (i.e., y-axis on histogram 108) and illustrates histogram 105 for
nighttime conditions, with pixel values ranging from about 25 to about 75,
with each pixel value corresponding to a specific frequency.
Because the histograms for the Day Light (DL) cluster are distinct
from the Low Light (LL) cluster of Zhu, including the frequency
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corresponding to each pixel value, any determination of whether a histogram
should be placed into the DL cluster would require a comparison to given
frequency corresponding to a predetermined pixel value. Accordingly, Zhu
discloses the limitation “determining whether the image is captured during
the daytime lighting conditions as a function of the aggregate value within
the predetermined category bin.”
Appellants argue “[w]hile Zhu describes determining a lighting
condition based on illumination intensity values in a distributed histogram,
Zhu does not teach the specific technique and associated limitations recited
in claim 1” and “[t]he Examiner appears to be applying Zhu based on the
end result of identifying the daylight lighting condition, and not on the
process/steps used to identify the lighting condition.” (App. Br. 9—10.)
However, as discussed previously, any comparison between two histograms
would require comparing the frequencies (i.e., the y-axis of the histograms)
at a predetermined pixel values (i.e., bins).
Therefore, we agree with the Examiner that Zhu describes the
limitation “determining whether the image is captured during the daytime
lighting conditions as a function of the aggregate value within the
predetermined category bin.”
Accordingly, we sustain the rejection of independent claim 1 under 35
U.S.C. § 102(b). Claim 6 depends from claim 1, and Appellants have not
presented any substantive arguments with respect to this claim. Therefore,
we sustain the rejection of claim 6 under 35 U.S.C. § 102(b), for the same
reasons discussed with respect to independent claim 1.
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Dependent Claim 2
We are unpersuaded by Appellants’ arguments (App. Br. 10—11; see
also Reply Br. 4) that Zhu does not describe the limitation “wherein the
determination that the image is captured during the daylight lighting
conditions is based on the aggregate number being less than a first
predetermined threshold,” as recited in dependent claim 2.
The Examiner found that the four categories of Zhu, including Night,
Low Light (LL), Daylight (DL) and Saturation, correspond to the limitation
“wherein the determination that the image is captured during the daylight
lighting conditions is based on the aggregate number being less than a first
predetermined threshold.” (Ans. 17; see also final Act. 7.) We agree with
the Examiner.
As discussed previously, figure 1 of Zhu illustrates histogram 108 for
daylight conditions, with pixel values ranging from about 150 to about 180
(i.e., bins) with each pixel value corresponding to a specific frequency (i.e.,
y-axis on the histogram) and illustrates histogram 105 for nighttime
conditions, with pixel values ranging from about 25 to about 75, with each
pixel value corresponding to a specific frequency. Lor example, from
figure 1, histogram 108 illustrates that for pixel values ranging from about
25 to about 75, the corresponding frequency is close to zero, and
accordingly, discloses the limitation “wherein the determination that the
image is captured during the daylight lighting conditions is based on the
aggregate number being less than a first predetermined threshold.”
Appellants argue that “[t]he Examiner alleges that the determination
performed by identifying the nearest centroid among the clusters implies that
the inherent thresholds transition from one category to the next” and
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“Applicant asserts that to anticipate the claim, the reference must teach each
of the limitations and not infer the limitations.” (App. Br. 10 (emphasis
omitted); see also Reply Br. 4.) Appellants further argue that “Zhu’s
technique of utilizing a centroid is a completely different technique than that
recited in claim 2 of determining whether the aggregate value of the
predetermined category bin of the cumulative histogram is less than a first
predetermined threshold” and “[w]hile Zhu describes a technique for
determining the lighting condition, the process is different from the claimed
process recited in claim 2.” (App. Br. 11.) However, as discussed
previously, histogram 108 of Zhu illustrates that for pixel values ranging
from about 25 to about 75, the corresponding frequency is close to zero, and
accordingly, Zhu discloses the limitation “wherein the determination that the
image is captured during the daylight lighting conditions is based on the
aggregate number being less than a first predetermined threshold.”
Therefore, we agree with the Examiner that Zhu describes the
limitation “wherein the determination that the image is captured during the
daylight lighting conditions is based on the aggregate number being less than
a first predetermined threshold.”
Accordingly, we sustain the rejection of dependent claim 2 under 35
U.S.C. § 102(b).
Dependent Claim 3
We are persuaded by Appellants’ arguments (App. Br. 11—12) that
Zhu does not describe the limitation “wherein the determination of whether
the captured image is obtained during the daytime lighting conditions further
comprises the step of determining whether the captured image includes a
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daylight blocking structure over the path of travel,” as recited in dependent
claim 3.
The Examiner found that the image of low light condition of Zhu,
which includes tunnels, corresponds to the limitation “wherein the
determination of whether the captured image is obtained during the daytime
lighting conditions further comprises the step of determining whether the
captured image includes a daylight blocking structure over the path of
travel.” (Ans. 19; see also Final Act. 8.) We do not agree.
Zhu explains that low light images “include images of dusk, dawn, or
in tunnels with low ambient lights.” (171.) Although the Examiner cited to
the “tunnels with low ambient lights” of Zhu, the Examiner has provided
insufficient evidence to support a finding that Zhu discloses the limitation
“wherein the determination of whether the captured image is obtained during
the daytime lighting conditions further comprises the step of determining
whether the captured image includes a daylight blocking structure over the
path of travel.” In particular, Zhu explains that such tunnel is associated
with other low light images, such as dusk or dawn, rather than “a daylight
blocking structure over the path of travel,” as claimed. (171.) Thus, the
Examiner had not demonstrated that Zhu discloses the limitation “wherein
the determination of whether the captured image is obtained during the
daytime lighting conditions further comprises the step of determining
whether the captured image includes a daylight blocking structure over the
path of travel.”
Accordingly, we are persuaded by Appellants’ arguments that “this
referenced section of Zhu fails to describe the determination of whether the
images include a daylight blocking structure captured during the daytime
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lighting conditions” and “[t]he term low ‘ambient’ lights refers to the
general lighting condition in a surrounding area, and that by itself does not
teach the limitation of determining whether an image was captured during
the daytime lighting condition while under a daylight blocking structure.”
(App. Br. 11.)
Therefore, we do not agree with the Examiner that Zhu describes the
limitation “wherein the determination of whether the captured image is
obtained during the daytime lighting conditions further comprises the step of
determining whether the captured image includes a daylight blocking
structure over the path of travel,” as recited in dependent claim 3.
Accordingly, we do not sustain the rejection of dependent claim 3
under 35 U.S.C. § 102(b).
§103 Rejection—Zhu
Dependent Claims 4 and 7
Claims 4 and 7 dependent from claim 3. We do not sustain the
rejection of claims 4 and 7 for the same reasons discussed with respect to
rejection of claim 3 under 35 U.S.C. § 102(b) as anticipated by Zhu.
Dependent Claim 8
Although Appellants nominally argue the rejection of dependent
claim 8 separately (App. Br. 14), the arguments presented do not point out
with particularity or explain why the limitations of this dependent claim are
separately patentable. Instead, Appellants merely argue that “[sjimilar to
Appellants’ arguments set forth in support of claim 1, there is no description
of an aggregate number within a predetermined category bin of the
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cumulative threshold being compared to a first predetermined threshold” and
“Appellant specifically utilizes a cumulative histogram as opposed to a
distributive histogram for enhancing the operations and results from the
described technique” {Id.) We are not persuaded by these arguments for the
reasons discussed with respect to claim 1, from which claim 8 depends.
Accordingly, we sustain this rejection.
Dependent Claim 9
We are persuaded by Appellants’ arguments (App. Br. 16—17) that
Zhu does not describe the limitation “determining whether the nighttime
lighting conditions include substantial lighting for illumination the path of
travel,” as recited in dependent claim 9.
The Examiner found the four categories of Zhu, including Night, Low
Light (LL), Daylight (DL) and Saturation, correspond to the limitation
“determining whether the nighttime lighting conditions include substantial
lighting for illumination the path of travel.” (Ans. 24; see also id. at 17, 19.)
We do not agree.
As discussed previously, figure 3 of Zhu illustrates “the type of image
and histogram associated with a particular cluster of images” (1 69),
including Night (| 70), Low Light (LL) (| 71), Day Light (DL) (| 72), and
Saturated (173). Although the Examiner cited to figure 3 of Zhu, including
the Night, Low Light (LL), Daylight (DL) and Saturation clusters, the
Examiner has provided insufficient evidence to support a finding that Zhu
teaches the limitation “determining whether the nighttime lighting
conditions include substantial lighting for illumination the path of travel.”
In particular, Zhu explains certain images are clustered with either Night or
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Low Light (LL) conditions, but is silent with respect lighting for either Night
or Low Light conditions. Thus, the Examiner has not demonstrated that Zhu
teaches the limitation “determining whether the nighttime lighting
conditions include substantial lighting for illumination the path of travel.”
Accordingly, we are persuaded by Appellants’ arguments that
“[w]hile Zhu describes a technique for determining whether the image
includes night, low light, daylight, or saturation, the technique is entirely
different from that recited in claim 9, and more specifically, there is no
determination of whether the path of travel during the nighttime lighting
condition includes substantial illumination.” (App. Br. 16—17.)
Thus, we do not agree with the Examiner that Zhu would have
rendered obvious dependent claim 9, which includes the limitation
“determining whether the nighttime lighting conditions include substantial
lighting for illumination the path of travel.”
Therefore, we do not sustain the rejection of dependent claim 9 under
35 U.S.C. § 103(a).
Claim 14
Although Appellants nominally argue the rejection of dependent
claim 14 separately (App. Br. 17), the arguments presented do not point out
with particularity or explain why the limitations of this dependent claim are
separately patentable. Instead, Appellants merely provide a conclusory
statement that “Zhu fails to describe capturing multiple images over a period
of time and cumulatively analyzing the multiple images for detecting the
daylight conditions” and “[wjhile Zhu describes analyzing a respective
image captured by the image capture device, there is no description in Zhu
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of cumulatively analyzing multiple images for detecting daylight
conditions.” (App. Br 17 (emphasis omitted).) Accordingly, Appellants
have not presented any substantive arguments with respect to this claim. See
In reLovin, 652 F.3d 1349, 1357 (Fed. Cir. 2011) (“[T]he Board reasonably
interpreted Rule 41.37 to require more substantive arguments in an appeal
brief than a mere recitation of the claim elements and a naked assertion that
the corresponding elements were not found in the prior art.”). We are not
persuaded by these arguments for the reasons discussed with respect to
claim 1, from which claim 14 depends. Accordingly, we sustain this
rejection.
Claims 15—20
Claims 15 and 16 recite limitations similar to those discussed with
respect to dependent claim 3. Claims 17—20 depend from claim 16. We do
not sustain the rejection of claims 15 and 16, as well as dependent
claims 17—20, for the same reasons discussed with respect to the rejection of
dependent claim 3 under 35 U.S.C. § 102(b).
§103 Rejection—Zhu and Wildervanck
Claim 5 depends from claim 4. Wildervanck was cited by the
Examiner for teaching the additional features of claim 5. (Ans. 10—11.)
However, the Examiner’s application of Wildervanck does not cure the
above noted deficiencies of Zhu. Accordingly, we do not sustain the
rejection of dependent claim 5 under 35 U.S.C. § 103(a).
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§103 Rejection—'/hit and Schofield
Claims 10-12
Claims 10-12 depend from claim 1 and Appellants have not presented
any additional substantive arguments with respect to these claims. (App.
Br. 22.) Therefore, we sustain the rejection of claims 10-12 under 35 U.S.C.
§ 103(a), for the same reasons discussed with respect to independent
claim 1.
Claim 13
We are unpersuaded by Appellants’ arguments (App. Br. 21—22; see
also Reply Br. 2—3) that the combination of Zhu and Schofield would not
have rendered obvious dependent claim 13, which includes the limitation
“wherein the selected region of interest represents an expected location of a
skyline within the captured image.”
The Examiner found that the photosensor elements of Schofield,
which detects portions of the scene just above the horizon, corresponds to
the limitation “wherein the selected region of interest represents an expected
location of a skyline within the captured image.” (Ans. 33; see also Final
Act. 39.) In particular, the Examiner further found that “[i]t is well-known
to the person of ordinary skill in the art at the time of the invention that the
Earth’s horizon would be the selected location of skyline where sky would
not be occluded.” (Ans. 33.) The Examiner concluded that “it would have
been obvious ... to modify the system disclosed by Zhu [to] add the
teachings of Schofield ... in order to selected region of interest represents
an expected location of a skyline within the captured image.” {Id.) We
agree with the Examiner.
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Zhu explains that “the upper third of the frames shows large variations
because of various objects that can occlude the sky, such as trees, mountains
or buildings.” (1 53.) Zhu further explains that “[tjhese variations make it
more complex to infer the lighting context” and “[consequently the lighting
context of an image will be defined from the histogram of its lower two-
thirds.” (Id.)
Schofield relates to “controlling the vehicle’s headlamps in response
to sensing the headlights of oncoming vehicles and taillights of leading
vehicles.” (| 2.) Schofield explains that “[vjehicle headlight dimming
control 12 additionally includes an ambient light-sensing circuit 84 which
receives an input from digital output signal 68” and “the photosensor
elements in the sensed subset include sensors that detect portions of the
forward-looking scene that are just above the earth’s horizon which is more
indicative of the ambient light condition.” (| 30.) Because the photosensor
element of Schofield detects the ambient light condition using the forward-
looking scene near the earth’s horizon, Schofield teaches the limitation
“wherein the selected region of interest represents an expected location of a
skyline within the captured image.”
A person of ordinary skill in the art would have recognized that
incorporating the known method of Schofield, in which using a forward-
looking scene near the earth’s horizon is used to determine ambient light,
with the known vision systems of Zhu for vehicle detection, would improve
Zhu by providing the advantage of selecting a region more indicative of the
ambient light condition. See KSR Int’l Co. v. Teleflex Inc., 550 U.S. 398,
417 (2007) (“[I]f a technique has been used to improve one device, and a
person of ordinary skill in the art would recognize that it would improve
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similar devices in the same way, using the technique is obvious unless its
actual application is beyond his or her skill.”). Thus, we agree with the
Examiner (Ans. 33) that modifying Zhu to incorporate Schofield would have
been obvious.
Appellants argue that Zhu teaches sensing ambient light conditions on
the earth’s horizon, whereas “Zhu specifically states that the sky is not
utilized and avoided because of complexity issues,” and accordingly, “Zhu
teaches away from the limitations of claim 13” and “Zhu and Schofield are
not combinable since Zhu specifically negates the use of the sky for
illumination analysis.” (App. Br. 22.) Contrary to Appellants’ arguments,
Zhu describes an embodiment that excludes selecting the upper third of
frames as a region of interest because large variations can be created in that
upper third by various objects occluding the sky, such as trees, mountains,
and buildings. (1 53.) Furthermore, the Examiner found, and Appellants do
not dispute, that it was well known to a person of ordinary skill in the art that
the horizon would not be a location where objects, such as trees, mountains,
and buildings, would occlude the sky and create large variations. (Ans. 33.)
Accordingly, Zhu would not teach away from its combination with Schofield
or the use of the horizon, as a selected region of interest.
Thus, we agree with the Examiner that the combination of Zhu and
Schofield would have rendered obvious dependent claim 13, which includes
the limitation “wherein the selected region of interest represents an expected
location of a skyline within the captured image.”
Accordingly, we sustain the rejection of dependent claim 13 under 35
U.S.C. § 103(a).
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DECISION
The Examiner’s decision rejecting claims 1, 2, and 6 under 35 U.S.C.
§ 102(b) is affirmed.
The Examiner’s decision rejecting claim 3 under 35 U.S.C. § 102(b) is
reversed.
The Examiner’s decision rejecting claims 8 and 10—14 under 35
U.S.C. § 103(a) is affirmed.
The Examiner’s decision rejecting claims 4, 5, 7, 9 and 15—20 under
35 U.S.C. § 103(a) is reversed.
No time period for taking any subsequent action in connection with
this appeal may be extended under 37 C.F.R. § 1.136(a)(l)(iv).
AFFIRMED-IN-PART
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