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 .
This is the first office action on the merits and is responsive to the papers filed 03/22/2024. Claims 1-14 are currently pending and examined below
Priority
Acknowledgment is made of applicant’s claim for foreign priority under 35 U.S.C. 119 (a)-(d).
Information Disclosure Statement
The information disclosure statements submitted by Applicant are in compliance with the provision of 37 CFR 1.97, 1.98 and MPEP § 609. They have been placed in the application file and the information referred to therein has been considered as to the merits.
Claim Objections
Claims 1, 7-8, 12 are objected to because of the following informalities:
Claim 1, line 5 “each of the illumination features is at least one at least partially extended feature” should be – each of the illumination features is at least partially extended feature—
Claim 7, lines 7, 11-12 “extended cavity diode laser” appears twice. The duplicate term should be deleted.
Claim 8, line 1 “the detector claim 1” should be – the detector according to claim 1—
Claim 12, lines 5-6 “wherein the illumination pattern comprises a plurality of illumination features” appears twice. The duplicate term should be deleted.
Appropriate correction is required.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claim 14 is rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
As to claim 14, the examiner finds it unclear what limitation is attempted to be required by simply listing a multitude of use environments for the claim 1. The claim fails to add any clear new step to claim 1. The claim amounts to what be considered as a “Use” claim, as such it is unclear what actual steps are delimiting how the method is actually practiced. Please see MPEP 2173.05(q). For examination purposes the examiner is interpreting that the detector merely need be capable of the intended use, and since no step or structural limitation is actually claimed essentially any prior art showing the same claimed method/detector is capable of the claimed uses.
Claim Rejections - 35 USC § 103
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.
Claims 1-5, 7-14 are rejected under 35 U.S.C. 103 as being unpatentable over Schick et al. (WO 2020187719 A1, “Schick”) in view of Parupati et al. (US 20200311448 A1, “Parupati”).
Regarding claim 1, Schick teaches a detector for material detection of at least one object (p. 3, ll. 25- 26; Claim 1), the detector comprising:
at least one projector for illuminating at least one object with at least one illumination pattern, wherein the illumination pattern comprises a plurality of illumination features (illumination source 124 illuminates object 112 with an illumination pattern and that the pattern may comprise a plurality of points serving as image features. See p. 74, ll. 13-15. See also, p. 8, ll. 42- 43; p. 9, ll. 1-2 and p. 11, ll. 17.), wherein each of the illumination features is at least one at least partially extended feature of the illumination pattern (Claims 15-16, p. 11, ll. 1- 40), wherein the illumination features have a first wavelength (p. 9, ll. 22; p. 73, ll. 13- 29.);
at least one sensor element having a matrix of optical sensors, the optical sensors each having a light-sensitive area, wherein each optical sensor is designed to generate at least one sensor signal in response to an illumination of its respective light-sensitive area by a light beam propagating from the object to the detector (Claim 1; p. 72, ll. 3–28; p. 5, ll. 1-3, at least one sensor element (116) comprising a matrix (118) of optical sensors (120), the optical sensors (120) each having a light-sensitive area (122), wherein the sensor element (116) is configured for recording at least one reflection image of a light beam originating from at least one object (112)),
wherein the sensor element is configured for imaging at least one reflection image comprising a plurality of reflection features generated by the object in response to the illumination pattern, wherein a reflection feature is a feature in an image plane generated by the object in response to illumination with at least one illumination feature, wherein each of the reflection features comprises a beam profile (Schick teaches that illumination source 124 illuminates object 112 with an illumination pattern comprising a plurality of points as image features. See Schick, p. 74, ll. 13- 16. Each optical sensor 120 generates a sensor signal in response to a reflection light beam 130 propagating from object 112, and sensor element 116 records the resulting pixel readings as a reflection image. Schick expressly states that, when the illumination pattern is a point pattern, the reflection image comprises points as reflection features, with the points resulting from reflection light beams 130 originating from object 112. See Schick, p. 74, ll. 26- 36. Schick further teaches that sensor element 116 records a beam profile of a reflection feature, and describes a spot-like reflection feature as having a spot profile and the beam profile as, for example, a trapezoidal, triangular, conical, or Gaussian beam profile. See Schick, p. 74, ll. 38- 43; p. 75, ll. 23- 33. See also Schick, claim 1, claim 15 and claim 24.),
at least one evaluation device (Fig. 1, evaluation device 132, p. 74, ll. 38–43; p. 75, ll. 1–39),
wherein the evaluation device is configured for determining at least one first material information of the object by evaluating the beam profile of at least one of the reflection features (Claim 1; p. 83, ll. 1- 4 and 6-28.).
Schick fails to explicitly teach
at least one flood light source configured for scene illumination, wherein the flood light source is configured for emitting the scene illumination having a second wavelength different from the first wavelength;
wherein the sensor element is configured for imaging at least one scene image of the object illuminated by the scene illumination;
wherein the evaluation device is configured for determining at least one second material information of the object by evaluating the scene image,
wherein the evaluation device is configured for determining the material of the object using the first material information and the second material information.
Parupati teaches that an imaging system may include multiple illumination sources comprising LED elements configured to illuminate a subject at different, non-overlapping wavelength ranges. Parupati further teaches synchronizing the illumination sources with an image sensor such that portions of a scene image are captured under respective first and second wavelengths. See Parupati [0025]- [0028] and [0041]- [0044]. Parupati teaches that live skin and spoof materials such as paper, silicone, and plastic exhibit different spectral responses to different wavelengths and that the received image is evaluated to determine whether it contains the expected reflectance response of live skin. See Parupati [0009] and [0039]. Thus, Parupati teaches obtaining second material information from a different-wavelength scene image and using that information to distinguish the material of the imaged object.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to modify Schick, as taught by Parupati, to include an additional LED illumination source configured to illuminate the scene at a second wavelength, acquire a scene image under the second wavelength illumination, and determine additional material information from the wavelength dependent reflectance characteristics of the scene image because Parupati teaches that different materials exhibit distinguishable spectral responses at different wavelengths. The modification would have predictably improved Schick's material-detection system by providing a complementary spectral-information channel in addition to Schick's beam-profile-based material-information channel, thereby improving material classification accuracy and reducing ambiguity when materials exhibit similar characteristics in only one measurement modality.
Schick in view of Parupati, teaches wherein the evaluation device is configured for determining the material of the object using the first material information and the second material information.
Schick teaches determining first material information from a beam profile of a reflection feature. See Schick, p. 75, ll. 30-39 and claim 1.
Parupati teaches determining additional material-related information from wavelength-dependent scene-image reflectance characteristics. See Parupati [0009], [0025]- [0028], and [0039].
A person of ordinary skill in the art would have understood that both information sources characterize material properties of the same object and therefore may be used together during material classification. Consequently, the modified Schick system would determine the material of the object using both Schick's beam-profile-derived material information and Parupati's wavelength dependent reflectance information.
Regarding claim 2, Schick in view of Parupati, teaches the detector according to claim 1, wherein the evaluation device is configured for using the second material information as an additional information channel for distinguishing between materials.
Schick teaches using a plurality of wavelengths to obtain additional measurements in other wavelength channels. See Schick, p. 73, ll. 24- 26. Parupati further teaches that live skin and spoof materials such as paper, silicon, and plastic exhibit different spectral responses at different wavelengths and that wavelength specific pixel information of the captured image is evaluated to determine whether an expected live skin reflectance response is present. See Parupati [0025]- [0028], [0039], and [0043]- [0044]. Thus, the second material information derived from the second-wavelength scene image provides an additional information channel for distinguishing between materials.
Regarding claim 3, Schick in view of Parupati, teaches the detector according to claim 1, wherein the detector is configured to distinguish between biological or non-biological material.
Schick teaches that the material classifier may distinguish biological material from non-biological material and describes distinguishing human biological tissue from artificial or non-living objects. See Schick, p. 4, ll. 1- 34; Fig. 2. Parupati further teaches distinguishing live face skin from non-biological spoof materials such as paper, silicon, and plastic based on their different wavelength-dependent reflectance responses. See Parupati [0009] and [0039].
Regarding claim 4, Schick in view of Parupati, teaches the detector according to claim 1, wherein the detector is configured to distinguish between skin and non-skin objects.
Schick teaches distinguishing human skin from artificial surfaces and materials, including foam, paper, wood, displays, screens, cloth, metal, and plastic. See Schick, p. 4, ll. 9- 34; Fig. 2. Parupati further teaches discriminating live face skin from spoof materials such as paper, silicon, and plastic based on different spectral-reflectance responses at different wavelengths. See Parupati [0009] and [0039].
Regarding claim 5, Schick in view of Parupati, teaches the detector according to claim 1, wherein the first wavelength and the second wavelength are different wavelengths in the infrared spectral range.
Schick teaches infrared and near-infrared illumination, including wavelengths from approximately 700- 1100 nm, and teaches using a plurality of wavelengths for additional wavelength channels. See Schick, p. 73, ll. 18- 26. Parupati teaches first and second different, at least partially non-overlapping representative wavelength ranges and expressly identifies the NIR spectrum of approximately 700- 1400 nm as an operating range. See Parupati [0025]- [0028].
Regarding claim 7, Schick in view of Parupati, teaches the detector according to claim 1, wherein the projector comprises a plurality of emitters, wherein the emitters comprise at least one emitter selected from the group consisting of at least one semiconductor laser, at least one double heterostructure laser, at least one external cavity laser, at least one separate confinement heterostructure laser, at least one quantum cascade laser, at least one distributed bragg reflector laser, at least one polariton laser, at least one hybrid silicon laser, at least one extended cavity diode laser, at least one quantum dot laser, at least one volume Bragg grating laser, at least one Indium Arsenide laser, at least one transistor laser, at least one diode pumped laser, at least one distributed feedback laser, at least one quantum well laser, at least one interband cascade laser, at least one Gallium Arsenide laser, at least one semiconductor ring laser, at least one extended cavity diode laser, and at least one vertical cavity surface-emitting laser (VCSEL).
Schick teaches that illumination source 124 may comprise a plurality of light sources and that those light sources may be laser emitters. Schick expressly identifies semiconductor, double-heterostructure, external-cavity, separate-confinement heterostructure, quantum-cascade, distributed-Bragg-reflector, polariton, hybrid-silicon, extended-cavity diode, quantum-dot, volume-Bragg-grating, indium-arsenide, transistor, diode-pumped, distributed-feedback, quantum-well, interband-cascade, gallium-arsenide, semiconductor-ring, and VCSEL laser sources. See Schick, p. 73, ll. 13- 16 and 30- 43.
Regarding claim 8 Schick in view of Parupati, teaches the detector claim 1, wherein the flood light source comprises at least one light-emitting-diode (LED).
Parupati teaches one or multiple illumination sources 115 configured to illuminate a subject during image capture and teaches that each illumination source may comprise one or more LED elements 120. See Parupati [0025] and Fig. 1. The LED source illuminates the subject generally for scene-image capture and therefore corresponds to the claimed flood light source comprising at least one LED.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to further modify Schick, as taught by Parupati, so that the additional scene-illumination source comprises at least one LED, because Parupati teaches that LED elements provide controllable illumination at different wavelength ranges for image capture and material-dependent spectral analysis. Using an LED for the flood-light source would have been a predictable implementation choice that permits rapid wavelength switching, compact integration with the imaging device, and efficient illumination of the subject while preserving Schick’s existing patterned projector for beam-profile analysis.
Regarding claim 9, Schick in view of Parupati, teaches the detector according to claim 1, wherein the evaluation device is configured for determining a longitudinal coordinate of at least one of the reflection features by analysis of its respective beam profile, wherein the analysis of a beam profile comprises evaluating a combined signal Q from the sensor signals associated with the reflection feature, wherein the evaluation device is configured for using at least one predetermined relationship between the combined signal Q and the longitudinal coordinate for determining the longitudinal coordinate.
Schick teaches recording a beam profile of a reflection feature, specifically a reflected light spot, and determining a longitudinal coordinate by evaluating a combined signal Q derived from sensor signals representing respective areas of that beam profile. See Schick, p. 74, ll. 38- 43; p. 76, ll. 28- 40; p. 77, ll. 1- 20. Schick further teaches using a predetermined functional relationship between Q and the distance or longitudinal coordinate z0, wherein z0 = z0(Q). See p. 77, ll. 21–27; claim 12.
Regarding claim 10, Schick in view of Parupati, teaches the detector according to claim 9, wherein the evaluation device is configured for deriving the combined signal Q by one or more of dividing the sensor signals, dividing multiples of the sensor signals, dividing linear combinations of the sensor signals.
Schick expressly teaches deriving combined signal Q by dividing sensor signals, dividing multiples of the sensor signals, or dividing linear combinations of the sensor signals. See Schick, p. 76, l. 40- p. 77, l. 3; p. 78, ll. 35- 43; claim 12.
Regarding claim 11, Schick in view of Parupati, teaches the detector according to claim 1, wherein the sensor element comprises at least one CCD chip and/or at least one CMOS chip.
Schick teaches that sensor element 116 may comprise one or more CCD and/or CMOS devices having a matrix of pixels and expressly identifies a CCD detector chip and a CMOS detector chip. See Schick, p. 72, ll. 10- 14 and 25- 28; claim 14.
Claim 12 is a method claim corresponding to device claim 1. It is rejected for the same reason.
Regarding claim 13, Schick in view of Parupati, teaches the method according to claim 12, wherein the method further comprises evaluating the sensor signals thereby determining a combined signal Q and determining a longitudinal coordinate of at least one of the reflection features by analysis of its respective beam profile, wherein the analysis of a beam profile comprises evaluating the combined signal Q from the sensor signals associated with the reflection feature, wherein the evaluation device is configured for using at least one predetermined relationship between the combined signal Q and the longitudinal coordinate for determining the longitudinal coordinate.
Schick teaches evaluating sensor signals associated with a reflection feature to derive a combined signal Q and determining a longitudinal coordinate of the reflection feature based on the combined signal. Specifically, Schick teaches that a beam profile of a reflected light spot is recorded by the sensor element and that signal values associated with different regions of the beam profile are processed to determine a combined signal Q. See Schick, p. 76, ll. 28- 40.
Schick further teaches deriving the longitudinal coordinate z0 of the reflection feature from the combined signal Q using a predetermined relationship between Q and the longitudinal coordinate, expressed as z0=z0(Q). See Schick, p. 77, ll. 1- 27. Schick additionally teaches that the combined signal Q is obtained from sensor signals corresponding to respective portions of the beam profile and that the resulting Q value is evaluated to determine the longitudinal coordinate of the reflection feature. See Schick, p. 76, l. 40 - p. 77, l. 3; claim 12; claim 24.
Regarding claim 14, Schick in view of Parupati, teaches a method of using the detector according to claim 1, the method comprising using the detector for a purpose, selected from the group consisting of a position measurement in traffic technology; an entertainment application; a security application; a surveillance application; a safety application; a human-machine interface application; a tracking application; a photography application; an imaging application or camera application; a mapping application for generating maps of at least one space; a homing or tracking beacon detector for vehicles; an outdoor application; a mobile application; a communication application; a machine vision application; a robotics application; a quality control application; a manufacturing application; and automotive application (Schick, p. 71, ll. 6- 13; claim 25).
Claim 6 is rejected under 35 U.S.C. 103 as being unpatentable over Schick in view of Parupati and Joshi et al. (US 20200250448 A1, “Joshi”).
Regarding claim 6, Schick in view of Parupati, fails to explicitly teach the detector according to claim 1, wherein the first wavelength is 940 nm and the second wavelength is 850 nm.
Schick teaches using multiple illumination wavelengths and additional wavelength channels for obtaining additional material-related measurements. See Schick, p. 73, ll. 18- 29. However, Schick does not expressly disclose selecting 940 nm and 850 nm.
Joshi teaches that human tissue exhibits significantly greater absorption around 940 nm than around 850 nm, whereas spoof materials such as printed photographs, displays, and masks do not exhibit the same spectral behavior. Joshi therefore captures a first image under illumination at approximately 940 nm and a second image under illumination at approximately 850 nm, and determines liveness based on the difference between the images. See Joshi [0021]- [0022], [0029]- [0035], Fig. 5, and claims 5, 16, and 25.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to further modify Schick, as taught by Joshi, to employ a first illumination wavelength of approximately 940 nm and a second illumination wavelength of approximately 850 nm because Joshi teaches that the difference in tissue absorption between those wavelengths produces a measurable spectral signature useful for distinguishing live skin from non-biological spoof materials.
Employing the 940 nm and 850 nm wavelength pair would have predictably improved the accuracy of Schick’s material-detection system by providing enhanced spectral separation between biological and non-biological materials and by supplying additional wavelength-dependent material information for the material-classification process.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Ce Liu (US 20110243450 A1), teaches material recognition from an image
Send et al. (US 20170363465 A1), teaches optical detector
Kilgore et al. (US 20070106160 A1), teaches Skin Detection Sensor
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/JEMPSON NOEL/Examiner, Art Unit 3645
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