During my investigations into Search and Rescue operations infrared sensors were mentioned as an alternative to RGB cameras. The contrast provided by temperature differences, like that of a person juxtaposed to ambient temperature, makes it easier to locate missing persons. I believe that software like Loc8 could help thermal imaging reach its potential in SAR operations. Loc8 was chosen due to my familiarity with it, and the ability to choose specific colors. Since thermal imagery shows temperature in false color based on the output settings desired, a specific temperature color could be selected and searched for. In this case a "white hot" scale was used, where the hottest item is shown in bright white and the coldest in dark black. While collecting images with a FLIR E95 I noticed that the temperature scale was changing with each image. Figures 1 and 2 below show an example of this.
Figure 1: Computer ambient
Figure 2: Computer with hot mug
Figure 1 shows a thermal image of a computer in sleep mode with only ambient temperature surrounding it. On the right side of the image it can be seen that the temperature scale goes from 66.8 at the coldest to 74.2 at the hottest. In this image the computer is the hottest object in the image and is white. In figure 2 I have introduced a mug of hot tea into the frame. The temperature scale has shifted to 67.6 on the low end and 123 at the high end. In this image the tea mug is the hottest object and is white. This means that the color used to find 70F in figure 1 would find a much higher temperature in figure 2, making Loc8 unusable for this scenario.
In order to allow Loc8 to properly function in this situation the images need to be put on the same temperature scale regardless of object temperatures. I found two ways to do this. The first option is to process images through the FLIR tools software after data collection. This allows you to see the temperature range of your data set and adjust the scale accordingly. The second option I found was to adjust the scale manually on the sensor. This would allow a preset color range to be used on any data set using this preset range. There is the risk that an object will be outside of this temperature range though. I took the second approach for this initial investigation, and set the range to between 50F and 121F. I then created a temperature color range of ~74F to ~100F in Loc8 using images, figures 3 and 4, with the hottest temperature displayed.
Figure 3: Low end color
Figure 4: High end color
I sampled the images near the point called out as the hottest points in each image, and used those samples for the color range. I then tried to automatically detect the residual heat from a hand print, and then asked someone to walk around while I gathered images in a hangar. Figure 5 shows the hand print and figures 6 and 7 shows the locating of the person in the hangar.
Figure 5: Detected hand print
Figure 6: Detected person 1
Figure 7: Detected person 2
Figure 5 shows that this software has potential to detect residual heat from objects, but also shows that the color range on the right has been detected. I was able to fix this in the other images by adjusting the settings in Loc8. Figures 6 and 7 show a person walking around the aircraft in the hangar. Figure 6 has highlighted the person's face above a wing, but that would have likely been visible without using Loc8.
In the future I hope to make my temperature sampling more accurate to hone in more accurately on certain temperatures.
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