# US 11,443,527 B2 · Material spectroscopy

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- Number: US 11,443,527 B2
- Document ID: US11443527B2
- Status: Granted
- Kind: B2
- Application number: 17/147,944
- Filed: 2021-01-13
- Published: 2022-07-14
- Granted: 2022-09-13
- Earliest claimed: 2021-01-13
- Assignees: Ford Global Technologies, LLC
- Applicants: Ford Global Technologies, LLC
- Inventors: Ali Hassani; Hamid M. Golgiri; Jonathan Diedrich; Hemanth Yadav Aradhyula
- Web page: https://patentgrep.com/patent/US11443527B2

## CPC

- G06V 10/751: {Comparing pixel values or logical combinations thereof, or feature values having positional relevance, e.g. template matching}
- G06V 10/50: by performing operations within image blocks; by using histograms, e.g. histogram of oriented gradients [HoG]; by summing image-intensity values; Projection analysis
- G06V 10/54: relating to texture
- G06V 20/58: Recognition of moving objects or obstacles, e.g. vehicles or pedestrians; Recognition of traffic objects, e.g. traffic signs, traffic lights or roads
- G06V 20/64: Three-dimensional [3D] objects
- G06V 40/162: {using pixel segmentation or colour matching}
- G06V 40/169: {Holistic features and representations, i.e. based on the facial image taken as a whole}
- G06V 40/172: {Classification, e.g. identification}
- G06V: IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING

## Abstract

A computer, including a processor and a memory, the memory including instructions to be executed by the processor to acquire a first image by illuminating a first object with a first light beam, determine a first measure based on a first number of pixels corresponding to the first object in the first image and determine a relative distance measure by comparing the first measure based on the first number of pixels corresponding to the first object to a second measure based on a second number of pixels corresponding to a second object in the first image. The instructions can include instructions to modify the first measure of pixel values based on the relative distance measure, perform a comparison of the modified first measure of pixel values to a third measure of pixel values determined from a second image of a second object, and when the comparison determines that the first measure is equal to the third measure of pixel values within a tolerance, determine that the first object and the second object are a same object.

## Claims

### Claim 1

A computer, comprising:
a processor; and
a memory, the memory including instructions executable by the processor to:
acquire a first image by illuminating a first object with a first light beam;
determine a first measure based on a first number of pixels corresponding to the first object in the first image;
determine a relative distance measure by comparing the first measure based on the first number of pixels corresponding to the first object to a second measure based on a second number of pixels corresponding to a second object in the first image;
modify the first measure of pixel values based on the relative distance measure;
perform a comparison of the modified first measure of pixel values to a third measure of pixel values determined from a second image of a second object; and
when the comparison determines that the modified first measure is equal to the third measure of pixel values within a tolerance, determine that the first object and the second object are a same object.

### Claim 2 (depends on 1)

The computer of claim 1, wherein the first light beam is a near infrared light beam.

### Claim 3 (depends on 2)

The computer of claim 2, wherein the first and second images are acquired with a camera that acquires near infrared pixels, red pixels, green pixels and blue pixels.

### Claim 4 (depends on 1)

The system of claim 1, wherein the first number of pixels corresponding to the first object is compared to the second number of pixels corresponding to the second object by multiplying a ratio of the second number of pixels to the first number of pixels by a compensation value.

### Claim 5 (depends on 1)

The system of claim 1, wherein the first number of pixels corresponding to the first object is compared to the second number of pixels corresponding to the second object by multiplying a square of a square root of a ratio of the second number of pixels to the first number of pixels by a compensation value.

### Claim 6 (depends on 1)

The system of claim 1, the instructions including further instructions to determine the first number of pixels corresponding to the first object by dividing the first image into a plurality of regions, wherein each region includes a compensation value determined by a neural network.

### Claim 7 (depends on 1)

The system of claim 1, the instructions including further instructions to determine the relative distance measure by measuring a difference in polarized light reflected by the object and background in the first image.

### Claim 8 (depends on 1)

The computer of claim 1, the instructions including further instructions to output the determination whether the first object and the second object are a same type of object.

### Claim 9 (depends on 1)

The computer of claim 1, the instructions including further instructions to, when the comparison determines that each of the first object and the second object is a human face, perform human identification testing.

### Claim 10 (depends on 9)

The computer of claim 9, the instructions including further instructions to, when the comparison determines that each of the first object and the second object is a human face and are the same object, enable operation of a vehicle.

### Claim 11 (depends on 1)

The computer of claim 1, wherein the first and second measures of pixel values are Gaussian parameters calculated on first and second histograms of pixel values included in first and second images, respectively.

### Claim 12 (depends on 11)

The computer of claim 11, wherein the first and second Gaussian parameters are calculated based on a Gaussian mixture model applied to the first and second histograms, respectively.

### Claim 13

A method, comprising:
acquiring a first image by illuminating a first object with a first light beam;
determining a first measure based on a first number of pixels corresponding to the first object in the first image;
determining a relative distance measure by comparing the first measure based on the first number of pixels corresponding to the first object to a second measure based on a second number of pixels corresponding to a second object in the first image;
modifying the first measure of pixel values based on the relative distance measure;
performing a comparison of the modified first measure of pixel values to a third measure of pixel values determined from a second image of a second object; and
when the comparison determines that the first measure is equal to the third measure of pixel values within a tolerance, determine that the first object and the second object are a same object.

### Claim 14 (depends on 13)

The method of claim 13, wherein the first light beam is a near infrared light beam.

### Claim 15 (depends on 14)

The method of claim 14, wherein the first and second images are acquired with a camera that acquires near infrared pixels, red pixels, green pixels and blue pixels.

### Claim 16 (depends on 13)

The method of claim 13, wherein the first number of pixels corresponding to the first object is compared to the second number of pixels corresponding to the second object by multiplying a ratio of the second number of pixels to the first number of pixels by a compensation value.

### Claim 17 (depends on 13)

The method of claim 13, wherein the first number of pixels corresponding to the first object is compared to the second number of pixels corresponding to the second object by multiplying a square of a square root of a ratio of the second number of pixels to the first number of pixels by a compensation value.

### Claim 18 (depends on 13)

The method of claim 13, further comprising determining the first number of pixels corresponding to the first object by processing the first image to remove perspective distortions, dividing the first image into a plurality of regions, wherein each region includes a compensation value determined by a neural network.

### Claim 19 (depends on 13)

The method of claim 13, further comprising determining the relative distance measure by measuring a difference in polarized light reflected by the object and background in the first image.

### Claim 20 (depends on 13)

The method of claim 13, further comprising outputting the determination whether the first object and the second object are a same type of object.