Determining a total number of people in an IR image obtained via an IR imaging system

1. A method for determining the number of living objects in an IR image obtained by an IR imaging system, the method comprising:

collecting a total of N intensity values for each pixel in an IR image said intensity values having been collected using a IR imaging system comprising an IR detection device and an IR Illuminator;

for each pixel in said IR image:

generating a ratio of said pixel's collected intensity values comprising:

[ I c ( i )− I c ( k )]/[ I c ( j )− I c ( k )],

where i, j, k are any N-band indices different from each other;

forming a threshold from said generated ratio; and

using said threshold to classify said pixel as being from a living or non-living object; and

determining a total number of living objects in said IR image based upon said pixel classifications.

2. The method of claim 1 , wherein said IR detection device is a single IR detection device, and wherein said IR Illuminator is a sequentially illuminating N-band illuminator (N≧3) with one fixed filter, said intensity value comprising:

I c ( i )=α∫ λ 1 λ 2 I s i (λ)[ T G 2 (λ) R o (λ)+η R G (λ)] T L (λ) D (λ) dλ+I b ,

where i=1 . . . N, such that i is the i th IR band from said illuminator that is sequentially illuminating, α is a constant that depends on an angle and distance from said illumination source, an attenuation of an IR wave in the air, and an integration time of said detecting device, I s i (λ) is the intensity of the i th based on the light source, I b is an intensity from a background light source such as that from the IR component of sunlight, R o (λ) is a reflectance of an object detected by said IR detection device, R G (λ) and T G (λ) are a reflectance and a transmittance of glass, otherwise R G (λ)=0 and T G (λ)=1, constant η is a measure of the percentage of light from said illuminator reflected from vehicle glass and received by said detector, otherwise η is zero, T L (λ) is a transmittance of said fixed filter, and D(λ) is a responsivity of said detection device.

3. The method of claim 1 , wherein said IR detection device is N detection devices having N band pass filters (N≧3), and said IR Illuminator has one illuminator covering a wavelength range of said filters, said intensity value comprising:

I c ( i )=α∫ λ 1 λ 2 I s (λ)[ T G 2 (λ) R o (λ)+η R G (λ)] T L i (λ) D (λ) dλ+I b ,

where i=1 . . . N, such that i is the i th IR band pass filter, α is a constant that depends on an angle and distance from said illumination source, an attenuation of an IR wave in the air, and an integration time of said detecting device, I s (λ) is the intensity of the light source, I b is a background intensity, R o (λ) is a reflectance of an object detected by said IR detection device, R G (λ) and T G (λ) are a reflectance and a transmittance of glass, otherwise R G (λ)=0 and T G (λ)=1, constant η is a measure of the percentage of light from said illuminator reflected from vehicle glass and received by said detector, otherwise η is zero, T i L (λ) is a transmittance of the i th filter, and D(λ) is a responsivity of said detecting device.

4. The method of claim 1 , wherein determining said total number of living objects in said IR image based upon said classified pixels comprises cross-referencing an intensity value associated with each of said pixels with at least one calculated intensity value using one known reflectance obtained from a storage device.

5. The method of claim 4 , wherein said storage device further contains any of a power spectra of said illuminator, a transmittance of a filter, and a responsivity curve of a detector on said detection device.

6. The method of claim 1 , further comprising:

combining any of said pixel intensity values to generated at least one new intensity value for said pixel;

producing a new ratio using said generated new pixel intensity values;

forming a new threshold from said ratio; and

using said new threshold to classify said pixel.

7. The method of claim 1 , wherein said IR image is motion corrected.

8. The method of claim 1 , wherein said living objects are human occupants in a motor vehicle.

9. A system for determining the number of living objects in an IR image obtained by an IR imaging system, the system comprising:

an IR imaging system comprising an IR detection device and an IR Illuminator;

a memory and a storage medium; and

a processor in communication with and said storage medium and said memory, said processor executing machine readable instructions for performing the method of:

collecting a total of N intensity values for each pixel in an IR image, said intensity values having been collected using said IR imaging system;

for each pixel in said IR image:

generating a ratio of said pixel's collected intensity values comprising:

[ I c ( i )− I c ( k )]/[ I c ( j )− I c ( k )],

where i, j, k are any N-band indices different from each other;

forming a threshold from said generated ratio; and

using said threshold to classify said pixel as being from a living or non-living object; and

determining a total number of living objects in said IR image based upon said pixel classifications.

10. The system of claim 9 , wherein said IR detection device is a single IR detection device, and wherein said IR Illuminator is a sequentially illuminating N-band illuminator (N≧3) with one fixed filter, said intensity value comprising:

I c ( i )=α∫ λ 1 λ 2 I s i (λ)[ T G 2 (λ) R o (λ)+η R G (λ)] T L (λ) D (λ) dλ+I b ,

where i=1 . . . N, such that i is the i th IR band from said illuminator that is sequentially illuminating, α is a constant that depends on an angle and distance from said illumination source, an attenuation of an IR wave in the air, and an integration time of said detecting device, I s i (λ) is the intensity of the i th band of the light source, I b is an intensity from a background light source such as that from the IR component of sunlight, R o (λ) is a reflectance of an object detected by said IR detection device, R G (λ) and T G (λ) are a reflectance and a transmittance of glass, otherwise R G (λ)=0 and T G (λ)=1, constant η is a measure of the percentage of light from said illuminator reflected from vehicle glass and received by said detector, otherwise η is zero, T L (λ) is a transmittance of said fixed filter, and D(λ) is a responsivity of said detection device.

11. The system of claim 9 , wherein said IR detection device is N detection devices having N band pass filters (N≧3), and said IR Illuminator has one illuminator covering a wavelength range of said filters, said intensity value comprising:

I c ( i )=α∫ λ 1 λ 2 I s (λ)[ T G 2 (λ) R o (λ)+η R G (λ)] T L i (λ) D (λ) dλ+I b ,

where i=1 . . . N, such that i is the i th IR band pass filter, α is a constant that depends on an angle and distance from said illumination source, an attenuation of an IR wave in the air, and an integration time of said detecting device, I s (λ) is the intensity of the light source, I b is a background intensity, R o (λ) is a reflectance of an object detected by said IR detection device, R G (λ) and T G (λ) are a reflectance and a transmittance of glass, otherwise R G (λ)=0 and T G (λ)=1, constant η is a measure of the percentage of light from said illuminator reflected from vehicle glass and received by said detector, otherwise η is zero, T i L (λ) is a transmittance of the i th filter, and D(λ) is a responsivity of said detecting device.

12. The system of claim 9 , wherein determining said total number of living objects in said IR image based upon said classified pixels comprises cross-referencing an intensity value associated with each of said pixels with at least one calculated intensity value using one known reflectance obtained from a storage device.

13. The system of claim 12 , wherein said storage device further contains any of a power spectra of said illuminator, a transmittance of a filter, and a responsivity curve of a detector on said detection device.

14. The system of claim 9 , further comprising:

combining any of said pixel intensity values to generated at least one new intensity value for said pixel;

producing a new ratio using said generated new pixel intensity values;

forming a new threshold from said ratio; and

using said new threshold to classify said pixel.

15. The system of claim 9 , wherein said IR image is motion corrected.

16. The system of claim 9 , wherein said living objects are human occupants in a motor vehicle.

17. A computer implemented method for determining the number of living objects in an IR image obtained by an IR imaging system, the method comprising:

collecting a total of N intensity values for each pixel in an IR image, said intensity values having been collected using a IR imaging system comprising an IR detection device and an IR Illuminator;

for each pixel in said IR image:

generating a ratio of said pixel's collected intensity values comprising:

[ I c ( i )− I c ( k )]/[ I c ( j )− I c ( k )],

where i, j, k are any N-band indices different from each other;

forming a threshold from said generated ratio; and

using said threshold to classify said pixel as being from a living or non-living object; and

determining a total number of living objects in said IR image based upon said pixel classifications.

18. The computer implemented method of claim 17 , wherein said IR detection device is a single IR detection device, and wherein said IR Illuminator is a sequentially illuminating N-band illuminator (N 3 ) with one fixed filter, said intensity value comprising:

I c ( i )=α∫ λ 1 λ 2 I s i (λ)[ T G 2 (λ) R o (λ)+η R G (λ)] T L (λ) D (λ) dλ+I b ,

where i=1 . . . N, such that i is the i th IR band from said illuminator that is sequentially illuminating, α is a constant that depends on an angle and distance from said illumination source, an attenuation of an IR wave in the air, and an integration time of said detecting device, I s i (λ) is the intensity of the i th band of the light source, I b is an intensity from a background light source such as that from the IR component of sunlight, R o (λ) is a reflectance of an object detected by said IR detection device, R G (λ) and T G (λ) are a reflectance and a transmittance of glass, otherwise R G (λ)=0 and T G (λ)=1, constant η is a measure of the percentage of light from said illuminator reflected from vehicle glass and received by said detector, otherwise η is zero, T L (λ) is a transmittance of said fixed filter, and D(λ) is a responsivity of said detection device.

19. The computer implemented method of claim 17 , wherein said IR detection device is N detection devices having N band pass filters (N 3 ), and said IR Illuminator has one illuminator covering a wavelength range of said filters, said intensity value comprising:

I c ( i )=α∫ λ 1 2 I s (λ)[ T G 2 (λ) R o (λ)+η R G (λ)] T L i (λ) D (λ) dλ+I b ,

where i=1 . . . N, such that i is the i th IR band pass filter, a is a constant that depends on an angle and distance from said illumination source, an attenuation of an IR wave in the air, and an integration time of said detecting device, I s (λ) is the intensity of the light source, I b is a background intensity, R o (λ) is a reflectance of an object detected by said IR detection device, R G (λ) and T G (λ) are a reflectance and a transmittance of glass, otherwise R G (λ)=0 and T G (λ)=1, constant η is a measure of the percentage of light from said illuminator reflected from vehicle glass and received by said detector, otherwise η is zero, T i L (λ) is a transmittance of the i th filter, and D(λ) is a responsivity of said detecting device.

20. The computer implemented method of claim 17 , wherein determining said total number of living objects in said IR image based upon said classified pixels comprises cross-referencing an intensity value associated with each of said pixels with at least one calculated intensity value using one known reflectance obtained from a storage device.

21. The computer implemented method of claim 20 , wherein said storage device further contains any of a power spectra of said illuminator, a transmittance of a filter, and a responsivity curve of a detector on said detection device.

22. The computer implemented method of claim 17 , further comprising:

combining any of said pixel intensity values to generated at least one new intensity value for said pixel;

producing a new ratio using said generated new pixel intensity values;

forming a new threshold from said ratio; and

using said new threshold to classify said pixel.

23. The computer implemented method of claim 17 , wherein said IR image is motion corrected.

24. The computer implemented method of claim 17 , wherein said living objects are human occupants in a motor vehicle.