J-M Deniel : Radioprotection 2024 , 59 ( 4 ), 327 – 337 335
Table 6 . Columns 3 and 4 : difference between the observed and the calculated irradiances . Column 5 : ∈ T error on estimated black body temperature . Column 6 : change in E IR , th as a function of ∈ T and : misalignment effects .
Black body Difference passing Error on
Temp . |
Dist . ZþZ 0 |
from E th |
from E IR , th |
T estime |
E IR , th |
° Cmm |
mm |
toE m |
to E IR , pic |
e T |
vse T |
|
97 |
– |
�13 % |
800 |
172 |
�42 % |
�12 % |
|
492 |
– |
-10% |
|
97 |
�10 % |
�11 % |
900 |
172 |
�17 % |
�6 % |
|
492 |
�20 % |
�4 % |
|
97 |
�11 % |
�14 % |
1,000 |
172 |
�16 % |
�27 % |
|
492 |
�20 % |
�12 % |
|
97 |
�10 % |
�40 % |
1,100 |
172 |
�11 % |
�25 % |
|
492 |
�18 % |
�15 % |
|
97 |
�13 % |
�9 % |
1,200 |
172 |
�11 % |
|
|
492 |
�20 % |
�9 % |
|
97 |
�6 % |
�7 % |
1,300 |
172 |
�3 % |
�9 % |
|
492 |
�16 % |
�10 % |
þ7 % |
þ35 % |
þ4.8 % |
þ23 % |
þ3.1 % |
þ15 % |
þ2.8 % |
þ13 % |
þ2.3 % |
þ10 % |
þ2 % |
þ9 % |
linearity range . For example , CCD sensors are known to be linear with observed radiance within [ 5 %; 90 %] of their maximum value . This means [ 13 ; 229 ] counts for 8-bit sensors , [ 205 ; 3,686 ] counts for 12-bit sensors . The second part of the solution is to avoid picture treatments , by using RAW picture data . Indeed , pictures at least undergo color balance or white balance ( Ramanath and Drew , 2014 ) and gamma correction ( Smith , 1995 ). Additional treatments tend to enhance pictures , especially in smartphones .
5 Conclusion
The proposed color picture analysis method estimates irradiance from incandescent opaque materials on [ 780 ; 3,000 nm ]. Our results show that the method is accurate enough to provide information about the risks for workers of being exposed to incandescent materials and to help employers prevent risks of cataract .
This method requires a device already present in the pocket of every preventer , making it virtually free . This may help to prevention from cataracts in various industrial sectors .
Several perspectives are currently planned to make this method genuinely usable in industry . For the method to become available on smartphones , the following conditions are essential : 1 The camera requires an easy and cheap calibration method . This is currently under investigation .
2 To ensure proper geometry conditions , especially in smartphones , the method should account for more complex lens models ( Kolb et al ., 1995 ) than a pinhole ( Tomasi , 2015 ).
3 It must be usable with sensors having a low dynamic range , for example through the use of bracketing techniques ( Halford , 2022 ).
In addition , the method ’ s usability will be improved by reduced assessment time . Currently , analyzing a single picture requires up to 20s on a laptop computer . As described in this paper , the method performs simple operations on matrices . Massively parallel computing by GPGPU ( Tarditi et al ., 2006 ) seems the perfect way to process these data in graphic cards and achieve real time processing . In addition to ease of use , this technique may make it possible to assess exposure at any moment over a period of time . This is necessary to estimate doses of irradiance during some steps of an industrial process ( i . e ., loading a furnace or forging a piece of metal ).
Lastly , it is interesting to investigate irradiance estimation using incandescent glass picture analysis . Colored bodies cannot represent incandescent glass for the following reasons : – glass is glossy and even specular ; it is not a perfect absorber ; – light is not only emitted from surfaces , but from everywhere inside ;
– the temperature gradient from within a material to its surface will change the intensity and the spectral distribution of the radiations emitted ;
– it is a both transparent and participatory medium .
Therefore , incandescent glass will need further investigation in terms of modeling and recognition , to protect workers in the glass industry .
Funding
This research did not receive any specific funding .