DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Priority
Acknowledgment is made of applicant’s claim for foreign priority under 35 U.S.C. § 119 (a)-(d). The certified copy has been filed in parent Application No. JP2021-153459, filed on 09/21/2021.
Claim Interpretation
The following is a quotation of 35 U.S.C. 112(f):
(f) Element in Claim for a Combination. – An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The following is a quotation of pre-AIA 35 U.S.C. 112, sixth paragraph:
An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The claims in this application are given their broadest reasonable interpretation using the plain meaning of the claim language in light of the specification as it would be understood by one of ordinary skill in the art. The broadest reasonable interpretation of a claim element (also commonly referred to as a claim limitation) is limited by the description in the specification when 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is invoked.
As explained in MPEP § 2181, subsection I, claim limitations that meet the following three-prong test will be interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph:
(A) the claim limitation uses the term “means” or “step” or a term used as a substitute for “means” that is a generic placeholder (also called a nonce term or a non-structural term having no specific structural meaning) for performing the claimed function;
(B) the term “means” or “step” or the generic placeholder is modified by functional language, typically, but not always linked by the transition word “for” (e.g., “means for”) or another linking word or phrase, such as “configured to” or “so that”; and
(C) the term “means” or “step” or the generic placeholder is not modified by sufficient structure, material, or acts for performing the claimed function.
Use of the word “means” (or “step”) in a claim with functional language creates a rebuttable presumption that the claim limitation is to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites sufficient structure, material, or acts to entirely perform the recited function.
Absence of the word “means” (or “step”) in a claim creates a rebuttable presumption that the claim limitation is not to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is not interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites function without reciting sufficient structure, material or acts to entirely perform the recited function.
Claim limitations in this application that use the word “means” (or “step”) are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action. Conversely, claim limitations in this application that do not use the word “means” (or “step”) are not being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action.
This application includes one or more claim limitations that do not use the word “means,” but are nonetheless being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, because the claim limitation(s) uses a generic placeholder that is coupled with functional language without reciting sufficient structure to perform the recited function and the generic placeholder is not preceded by a structural modifier. Such claim limitations are: “a distinction detector configured to distinguish and detect,” “an intensity identifier configured to identify,” “a validity determiner configured to determine,” and “a vehicle detector configured to detect” in claim 1; “a vehicle recognizer configured to recognize,” “the vehicle recognizer is capable of recognizing,” and “the vehicle recognizer is incapable of recognizing the vehicle” in claim 2; “the vehicle detector is configured to detect” in claim 3; “the vehicle detector is configured not to detect,” “the intensity identifier identifies,” and “to detect the vehicle when the intensity identifier identifies” in claim 4; the vehicle detector is configured not to detect,” “the validity determine determines,” “to detect the vehicle when the validity determiner determines,” and “the intensity identifier identifies” in claims 5 and 6; “the validity determiner is configured to determine” in claim 7.
Because this/these claim limitation(s) is/are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, it/they is/are being interpreted to cover the corresponding structure described in the specification (See Applicant’s Spec. ¶32. Applicant discloses an image processing device comprising a distinction detector, an intensity identifier, and a validity determiner.) as performing the claimed function, and equivalents thereof.
If applicant does not intend to have this/these limitation(s) interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, applicant may: (1) amend the claim limitation(s) to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph (e.g., by reciting sufficient structure to perform the claimed function); or (2) present a sufficient showing that the claim limitation(s) recite(s) sufficient structure to perform the claimed function so as to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph.
Claim Objections
Claim 5 is objected to because of the following informalities: the limitation reads “the vehicle detector s configured…” Appropriate correction is required.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claims 1, 3, 6 and 10–12 are rejected under 35 U.S.C. § 103 as being unpatentable over Day et al. (U.S. 10,915,765 B2) in view of Kasaoki (U.S. 10,037,473 B2).
Regarding claim 1, Day discloses a vehicle detection device comprising:
an image obtainer configured to detect, with a light receiving element, a reflected light of a light irradiated to a detection area to obtain a reflected light image representing an intensity distribution of the reflected light, and (Per Fig. 1B, Day’s LIDAR system discloses an image where dots represent intensity—i.e., how much light returns in distance. Day col. 16 lines 48–63. In addition to location, each gray dot may also be associated with different types of information, for example, intensity (e.g., how much light returns back from that location),)
detect, with the light receiving element, an ambient light, (an ambient light construed as a secondary light source) which does not include the reflected light, in the detection area to obtain a background light image representing an intensity distribution of an ambient light; (Per Fig. 2C, Day’s LIDAR system 100 comprises primary 112A and secondary light sources 112B. He discloses that light sources are not active at the same time to project light patterns. Ibid. col. 20 lines 29–49. An interleave pattern means that the light sources are not active at the same time which may mitigate mutual interference.)
a distinction detector configured to distinguish and detect, from the background light image obtained by the image obtainer, a vehicle area (vehicle area construed as a region of non-interest within a field of view 120), which is estimated as likely to be a vehicle, and a parts area, (a parts area construed as a region of interest within the field of view) which is estimated as likely to be a specific vehicle part in which an intensity of the reflected light tends to be high; (Per Fig. 5B, Day’s processing unit 108 discloses an identification of regions of interest and non-interest within the field of view 120 given that his detectors 410 are either enabled or disabled, with which sensor sensitivity for range detection is calculated. Ibid. col. 35 line 37 – col. 36 line 7. [p]rocessing unit 108 may activate detectors 410 where a region of interest is expected and disable detectors 410 where regions of non-interest are expected… e.g., increasing sensor sensitivity for long range detection where the reflected power is low.)
an intensity identifier configured to identify a magnitude of a light intensity of each of the background light image and the reflected light image, which is obtained by the image obtainer, in the vehicle area, which is detected by the distinction detector. (Per Fig. 6C, Day discloses feature extraction in the captured image data to detect objects. Ibid. col. 38 lines 20–54. “[e]xtracting information” may include any process by which information associated with objects, individuals, locations, events, etc., is identified in the captured image data…)
However, Day fails to specifically disclose a validity determiner configured to determine validity of arrangement of the parts area based on the intensity distribution of the reflected light image, which is obtained by the image obtainer, in the parts area, which is detected by the distinction detector; and a vehicle detector configured to detect the vehicle by using the magnitude of the light intensity of each of the background light image and the reflected light image, which is identified by the intensity identifier and the validity of the arrangement of the parts area, which is determined by the validity determiner.
In related art, Kasaoki discloses a validity determiner configured to determine validity of arrangement of the parts area based on the intensity distribution of the reflected light image, which is obtained by the image obtainer, in the parts area, which is detected by the distinction detector; and (Per Fig. 7, Kasaoki discloses a color image and a second image to determine color thresholds where a region is detected having a higher intensity. Kasaoki col. 12 lines 10–39. [b]ased on the sum of any color threshold and any other color threshold having higher intensity (the lightness) than that color threshold is to appropriately determine a region having a higher intensity than any of the predetermined color thresholds.)
a vehicle detector configured to detect the vehicle by using the magnitude of the light intensity of each of the background light image and the reflected light image, which is identified by the intensity identifier and the validity of the arrangement of the parts area, which is determined by the validity determiner. (Per Fig. 2, Kasaoki’s candidate identifier 166 correlates a vehicle region to an identified candidate region with a light source. Ibid. col. 12 line 65 – col. 13 line 5. The candidate identifier 166 may further associate the vehicle region identified based on the first image with the light-emission source candidate identified based on the second image.)
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date to incorporate the teachings of Kasaoki into the teachings of Day to accurately identify a light source of a vehicle in exterior environment. Ibid. col. 2 lines 1–3.
Regarding claim 10, Day discloses a vehicle detection method implemented by at least one processor, the vehicle method comprising:
detecting, in an image obtainer process, with a light receiving element, a reflected light of a light irradiated to a detection area to obtain a reflected light image representing an intensity distribution of the reflected light, and (Per Fig. 1B, Day’s LIDAR system discloses an image where dots represent intensity—i.e., how much light returns in distance. Day col. 16 lines 48–63. In addition to location, each gray dot may also be associated with different types of information, for example, intensity (e.g., how much light returns back from that location),)
detecting, in the image obtainer process, with the light receiving element, an ambient light, (an ambient light construed as a secondary light source) which does not include the reflected light, in the detection area to obtain a background light image representing an intensity distribution of an ambient light; (Per Fig. 2C, Day’s LIDAR system 100 comprises primary 112A and secondary light sources 112B. He discloses that light sources are not active at the same time to project light patterns. Ibid. col. 20 lines 29–49. An interleave pattern means that the light sources are not active at the same time which may mitigate mutual interference.)
distinguishing and detecting, in a distinction detector process, from the background light image obtained by the image obtainer, a vehicle area (vehicle area construed as a region of non-interest within a field of view 120), which is estimated as likely to be a vehicle, and a parts area, (a parts area construed as a region of interest within the field of view) which is estimated as likely to be a specific vehicle part in which an intensity of the reflected light tends to be high; (Per Fig. 5B, Day’s processing unit 108 discloses an identification of regions of interest and non-interest within the field of view 120 given that his detectors 410 are either enabled or disabled, with which sensor sensitivity for range detection is calculated. Ibid. col. 35 line 37 – col. 36 line 7. [p]rocessing unit 108 may activate detectors 410 where a region of interest is expected and disable detectors 410 where regions of non-interest are expected… e.g., increasing sensor sensitivity for long range detection where the reflected power is low.)
identifying, in an intensity identifier process, magnitude of a light intensity of each of the background light image and the reflected light image, which is obtained by the image obtainer, in the vehicle area, which is detected by the distinction detector. (Per Fig. 6C, Day discloses feature extraction in the captured image data to detect objects. Ibid. col. 38 lines 20–54. “[e]xtracting information” may include any process by which information associated with objects, individuals, locations, events, etc., is identified in the captured image data…)
However, Day fails to specifically disclose determining, in a validity determiner process, validity of arrangement of the parts area based on the intensity distribution of the reflected light image, which is obtained in the image obtainer process, in the parts area, which is detected in the distinction detector process; and detecting, in a vehicle detector process, the vehicle by using the magnitude of the light intensity of each of the background light image and the reflected light image, which is identified in the intensity identifier process, and the validity of the arrangement of the parts area, which is determined in the validity determiner process.
In related art, Kasaoki discloses determining, in a validity determiner process, validity of arrangement of the parts area based on the intensity distribution of the reflected light image, which is obtained in the image obtainer process, in the parts area, which is detected in the distinction detector process; and (Per Fig. 7, Kasaoki discloses a color image and a second image to determine color thresholds where a region is detected having a higher intensity. Kasaoki col. 12 lines 10–39. [b]ased on the sum of any color threshold and any other color threshold having higher intensity (the lightness) than that color threshold is to appropriately determine a region having a higher intensity than any of the predetermined color thresholds.)
detecting, in a vehicle detector process, the vehicle by using the magnitude of the light intensity of each of the background light image and the reflected light image, which is identified in the intensity identifier process, and the validity of the arrangement of the parts area, which is determined in the validity determiner process. (Per Fig. 2, Kasaoki’s candidate identifier 166 correlates a vehicle region to an identified candidate region with a light source. Ibid. col. 12 line 65 – col. 13 line 5. The candidate identifier 166 may further associate the vehicle region identified based on the first image with the light-emission source candidate identified based on the second image.)
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date to incorporate the teachings of Kasaoki into the teachings of Day to accurately identify a light source of a vehicle in exterior environment. Ibid. col. 2 lines 1–3.
Regarding claim 11, Day discloses a non-transitory computer readable medium storing a vehicle detection program comprising instructions configured to be executed by at least one processor, the instructions configured to, when executed by the at least one processor, cause the at least one processor to:
detect, in an image obtainer process, with a light receiving element, a reflected light of a light irradiated to a detection area to obtain a reflected light image representing an intensity distribution of the reflected light, and (Per Fig. 1B, Day’s LIDAR system discloses an image where dots represent intensity—i.e., how much light returns in distance. Day col. 16 lines 48–63. In addition to location, each gray dot may also be associated with different types of information, for example, intensity (e.g., how much light returns back from that location),)
detect, in the image obtainer process, with the light receiving element, an ambient light, (an ambient light construed as a secondary light source) which does not include the reflected light, in the detection area to obtain a background light image representing an intensity distribution of an ambient light; (Per Fig. 2C, Day’s LIDAR system 100 comprises primary 112A and secondary light sources 112B. He discloses that light sources are not active at the same time to project light patterns. Ibid. col. 20 lines 29–49. An interleave pattern means that the light sources are not active at the same time which may mitigate mutual interference.)
distinguish and detect, in a distinction detector process, from the background light image obtained by the image obtainer, a vehicle area (vehicle area construed as a region of non-interest within a field of view 120), which is estimated as likely to be a vehicle, and a parts area, (a parts area construed as a region of interest within the field of view) which is estimated as likely to be a specific vehicle part in which an intensity of the reflected light tends to be high; (Per Fig. 5B, Day’s processing unit 108 discloses an identification of regions of interest and non-interest within the field of view 120 given that his detectors 410 are either enabled or disabled, with which sensor sensitivity for range detection is calculated. Ibid. col. 35 line 37 – col. 36 line 7. [p]rocessing unit 108 may activate detectors 410 where a region of interest is expected and disable detectors 410 where regions of non-interest are expected… e.g., increasing sensor sensitivity for long range detection where the reflected power is low.)
identify, in an intensity identifier process, magnitude of a light intensity of each of the background light image and the reflected light image, which is obtained by the image obtainer, in the vehicle area, which is detected by the distinction detector. (Per Fig. 6C, Day discloses feature extraction in the captured image data to detect objects. Ibid. col. 38 lines 20–54. “[e]xtracting information” may include any process by which information associated with objects, individuals, locations, events, etc., is identified in the captured image data…)
However, Day fails to specifically disclose determine, in a validity determiner process, validity of arrangement of the parts area based on the intensity distribution of the reflected light image, which is obtained in the image obtainer process, in the parts area, which is detected in the distinction detector process; and detect, in a vehicle detector process, the vehicle by using the magnitude of the light intensity of each of the background light image and the reflected light image, which is identified in the intensity identifier process, and the validity of the arrangement of the parts area, which is determined in the validity determiner process.
In related art, Kasaoki discloses determine, in a validity determiner process, validity of arrangement of the parts area based on the intensity distribution of the reflected light image, which is obtained in the image obtainer process, in the parts area, which is detected in the distinction detector process; and (Per Fig. 7, Kasaoki discloses a color image and a second image to determine color thresholds where a region is detected having a higher intensity. Kasaoki col. 12 lines 10–39. [b]ased on the sum of any color threshold and any other color threshold having higher intensity (the lightness) than that color threshold is to appropriately determine a region having a higher intensity than any of the predetermined color thresholds.)
detect, in a vehicle detector process, the vehicle by using the magnitude of the light intensity of each of the background light image and the reflected light image, which is identified in the intensity identifier process, and the validity of the arrangement of the parts area, which is determined in the validity determiner process. (Per Fig. 2, Kasaoki’s candidate identifier 166 correlates a vehicle region to an identified candidate region with a light source. Ibid. col. 12 line 65 – col. 13 line 5. The candidate identifier 166 may further associate the vehicle region identified based on the first image with the light-emission source candidate identified based on the second image.)
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date to incorporate the teachings of Kasaoki into the teachings of Day to accurately identify a light source of a vehicle in exterior environment. Ibid. col. 2 lines 1–3.
Regarding claim 12, Day discloses a vehicle detection device comprising:
at least one processor; and (Fig. 25C, a CPU 3234)
at least one memory storing instructions configured to, when executed by the processor, cause the at least one processor to: (Fig. 23A, LIDAR system 4100. Day col. 72 lines 11–26.)
detect, in an image obtainer process, with a light receiving element, a reflected light of a light irradiated to a detection area to obtain a reflected light image representing an intensity distribution of the reflected light, and (Per Fig. 1B, Day’s LIDAR system discloses an image where dots represent intensity—i.e., how much light returns in distance. Day col. 16 lines 48–63. In addition to location, each gray dot may also be associated with different types of information, for example, intensity (e.g., how much light returns back from that location),)
detect, in the image obtainer process, with the light receiving element, an ambient light, (an ambient light construed as a secondary light source) which does not include the reflected light, in the detection area to obtain a background light image representing an intensity distribution of an ambient light; (Per Fig. 2C, Day’s LIDAR system 100 comprises primary 112A and secondary light sources 112B. He discloses that light sources are not active at the same time to project light patterns. Ibid. col. 20 lines 29–49. An interleave pattern means that the light sources are not active at the same time which may mitigate mutual interference.)
distinguish and detect, in a distinction detector process, from the background light image obtained by the image obtainer, a vehicle area (vehicle area construed as a region of non-interest within a field of view 120), which is estimated as likely to be a vehicle, and a parts area, (a parts area construed as a region of interest within the field of view) which is estimated as likely to be a specific vehicle part in which an intensity of the reflected light tends to be high; (Per Fig. 5B, Day’s processing unit 108 discloses an identification of regions of interest and non-interest within the field of view 120 given that his detectors 410 are either enabled or disabled, with which sensor sensitivity for range detection is calculated. Ibid. col. 35 line 37 – col. 36 line 7. [p]rocessing unit 108 may activate detectors 410 where a region of interest is expected and disable detectors 410 where regions of non-interest are expected… e.g., increasing sensor sensitivity for long range detection where the reflected power is low.)
identify, in an intensity identifier process, magnitude of a light intensity of each of the background light image and the reflected light image, which is obtained by the image obtainer, in the vehicle area, which is detected by the distinction detector. (Per Fig. 6C, Day discloses feature extraction in the captured image data to detect objects. Ibid. col. 38 lines 20–54. “[e]xtracting information” may include any process by which information associated with objects, individuals, locations, events, etc., is identified in the captured image data…)
However, Day fails to specifically disclose determine, in a validity determiner process, validity of arrangement of the parts area based on the intensity distribution of the reflected light image, which is obtained in the image obtainer process, in the parts area, which is detected in the distinction detector process; and detect, in a vehicle detector process, the vehicle by using the magnitude of the light intensity of each of the background light image and the reflected light image, which is identified in the intensity identifier process, and the validity of the arrangement of the parts area, which is determined in the validity determiner process.
In related art, Kasaoki discloses determine, in a validity determiner process, validity of arrangement of the parts area based on the intensity distribution of the reflected light image, which is obtained in the image obtainer process, in the parts area, which is detected in the distinction detector process; and (Per Fig. 7, Kasaoki discloses a color image and a second image to determine color thresholds where a region is detected having a higher intensity. Kasaoki col. 12 lines 10–39. [b]ased on the sum of any color threshold and any other color threshold having higher intensity (the lightness) than that color threshold is to appropriately determine a region having a higher intensity than any of the predetermined color thresholds.)
detect, in a vehicle detector process, the vehicle by using the magnitude of the light intensity of each of the background light image and the reflected light image, which is identified in the intensity identifier process, and the validity of the arrangement of the parts area, which is determined in the validity determiner process. (Per Fig. 2, Kasaoki’s candidate identifier 166 correlates a vehicle region to an identified candidate region with a light source. Ibid. col. 12 line 65 – col. 13 line 5. The candidate identifier 166 may further associate the vehicle region identified based on the first image with the light-emission source candidate identified based on the second image.)
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date to incorporate the teachings of Kasaoki into the teachings of Day to accurately identify a light source of a vehicle in exterior environment. Ibid. col. 2 lines 1–3.
Regarding claim 3, Day as modified by Kasaoki, discloses the vehicle detection device, wherein the vehicle detector is configured to detect the vehicle when the intensity identifier identifies that the light intensity of the reflected light image is high. (Per Fig. 7, Kasaoki discloses a color image and a second image to determine color thresholds where a region is detected having a higher intensity. Kasaoki col. 12 lines 10–39. [b]ased on the sum of any color threshold and any other color threshold having higher intensity (the lightness) than that color threshold is to appropriately determine a region having a higher intensity than any of the predetermined color thresholds.)
Regarding claim 6, Day as modified by Kasaoki, the vehicle detection device, wherein the vehicle detector is configured to not to detect the vehicle when the validity determiner determines that the parts area does not have validity, and to detect the vehicle when the validity determiner determines that the arrangement of the parts area has validity. (Per Fig. 2, Kasaoki’s candidate identifier 166 correlates a vehicle region to an identified candidate region with a light source. Kasaoki col. 12 line 65 – col. 13 line 5. The candidate identifier 166 may further associate the vehicle region identified based on the first image with the light-emission source candidate identified based on the second image.)
Claims 2 and 4 are rejected under 35 U.S.C. § 103 as being unpatentable over Day in view of Kasaoki and further in view of Iriba (U.S. 11,628,762 B2).
Regarding claim 2, Day as modified by Kasaoki, discloses the vehicle detection device further comprising:
a vehicle recognizer configured to recognize a vehicle based on a 3D detection process, wherein the 3D detection process indirectly uses at least one of the background light image or the reflected light image obtained by the image obtainer or directly uses the reflected light image obtained by the image obtainer. (Per Fig. 25B, Day’s processor 118 discloses depth image comprising 3D model of scene. Day col. 33 line 50 – col. 34 line 7. [p]oint cloud model, polygon mesh, depth image (holding depth information for each pixel of an image or of a 2D array), or any other type of 3D model of a scene.)
However, Day as modified by Kasaoki, fails to specifically disclose the vehicle detector is configured to detect the vehicle, when the vehicle recognizer is capable of recognizing the vehicle, and detect the vehicle, even when the vehicle recognizer is incapable of recognizing the vehicle, by using a level of the light intensity of the background light image and a level of the light intensity of the reflected light image identified by the intensity identifier and
the validity of the arrangement of the parts area determined by the validity determiner.
In related art, Iriba discloses the vehicle detector is configured to detect the vehicle, when the vehicle recognizer is capable of recognizing the vehicle, and detect the vehicle, even when the vehicle recognizer is incapable of recognizing the vehicle, by using a level of the light intensity of the background light image and a level of the light intensity of the reflected light image identified by the intensity identifier and the validity of the arrangement of the parts area determined by the validity determiner. (Per Fig. 10F, Iriba’s luminance analyzing unit 1008 discloses an illuminated region 1102a of an obtained image IMG determining whether it detects low intensity thereof such that the signal does not consider a high luminance object. Iriba col. 20 lines 4–21. The first sign 1102 is not a self-luminous object. Therefore, the first sign 1102 is not captured as a high luminance object in the obtained image IMG.)
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date to incorporate the teachings of Iriba into the teachings of Day and Kasaoki to detect a front vehicle in a region ahead of a vehicle. Ibid. col. 2 line 61 – col. 3 line 9.
Regarding claim 4, Day as modified by Kasaoki, discloses the claimed invention, but fails to specifically disclose the vehicle device, wherein the vehicle detector is configured not to detect the vehicle, when the intensity identifier identifies that only the light intensity of the reflected light image is low among the reflected light image and the background light image, and
to detect the vehicle when the intensity identifier identifies that the light intensity of both the reflected light image and the background light image is low.
In related art, Iriba discloses the vehicle device, wherein the vehicle detector is configured not to detect the vehicle, when the intensity identifier identifies that only the light intensity of the reflected light image is low among the reflected light image and the background light image, and to detect the vehicle when the intensity identifier identifies that the light intensity of both the reflected light image and the background light image is low. (Per Fig. 10F, Iriba’s luminance analyzing unit 1008 discloses an illuminated region 1102a of an obtained image IMG determining whether it detects low intensity thereof such that the signal does not consider a high luminance object. Iriba col. 20 lines 4–21. The first sign 1102 is not a self-luminous object. Therefore, the first sign 1102 is not captured as a high luminance object in the obtained image IMG.)
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date to incorporate the teachings of Iriba into the teachings of Day and Kasaoki to detect a front vehicle in a region ahead of a vehicle. Ibid. col. 2 line 61 – col. 3 line 9.
Claims 8–9 are rejected under 35 U.S.C. § 103 as being unpatentable over Day in view of Kasaoki and further in view of Satoyuki (JP2016183922 A).
Regarding claim 8, Day as modified by Kasaoki, discloses the claimed invention, but fails to specifically disclose the vehicle detection device, wherein the image obtainer is configured to detect, with the light receiving element having sensitivity in a non-visible region, the reflected light of the light irradiated to the detection area to obtain the reflected light image representing the intensity distribution of the reflected light, and detect, with the light receiving element that is same as the light receiving element at a timing different from detection of the reflected light, the ambient light, which does not include the reflected light, in the detection area to obtain the background light image representing the intensity distribution of the ambient light.
In related art, Satoyuki discloses the vehicle detection device, wherein the image obtainer is configured to detect, with the light receiving element having sensitivity in a non-visible region, the reflected light of the light irradiated to the detection area to obtain the reflected light image representing the intensity distribution of the reflected light, and (Per Fig. 3, Satoyuki’s distance image sensor 14B discloses photodetection group which is not detected by his detection unit 36 such that corresponding distance thereto is derived. Satoyuki ¶41. [t]he distance image generation unit 42 uses the output value of the first photodetector VH in the first photodetector group 52VH for which saturation has not been detected by the saturation detection unit 36…)
detect, with the light receiving element that is same as the light receiving element at a timing different from detection of the reflected light, the ambient light, which does not include the reflected light, in the detection area to obtain the background light image representing the intensity distribution of the ambient light. (Per Fig. 2, Satoyuki’s image sensor 14A discloses a group of high-sensitivity photo detection and low-sensitivity photo detection at different sensitivity—i.e., different timing. Ibid. ¶33. [a] group of high-sensitivity photodetectors H (high-sensitivity photodetector group 51H) and a group of low-sensitivity photodetectors L (low-sensitivity photodetector group 51L), each having different sensitivities.)
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date to incorporate the teachings of Satoyuki into the teachings of Day and Kasaoki to simultaneously acquire distance of nearby object and a far-away one within measurable distance. Ibid. ¶9.
Regarding claim 9, it has been rejected in the same manner as claim 8.
Allowable Subject Matter
Claims 5 and 7 are objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Lu (U.S. 11,170,228 B2) discloses a vehicle ranging system.
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/BENEDICT E LEE/Examiner, Art Unit 2665
/Stephen R Koziol/Supervisory Patent Examiner, Art Unit 2665
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