Axis Communications Q2901-E Thermal network cameras Performance consideration - Page 4

Figure 2: Example of an Axis thermal camera used for motion detection. 2.2 Tripwire detection A virtual line can be placed in the image of the thermal network camera, see Figure 3. The virtual line will act as a tripwire. If an object crosses the virtual tripwire, the thermal network camera can trigger another camera as in the motion detection example. Figure 3: Example of a virtual tripwire. Integrating thermal network cameras with intelligent video applications has many advantages. However, in order to get the optimum use of thermal network cameras other things will have to be considered than when using conventional network cameras. Definition of detection range, number of pixels across the object, and the surrounding environment need to be considered. These parameters are of special importance when integrating with an intelligent video application. 3. Definition of detection range according to Johnson's criteria The resolution required to detect an object is stated in pixels and is determined by means of Johnson's criteria. John Johnson, a US military scientist, developed this method for predicting the performance of sensor systems during the 1950's. An object can be a person, typically defined with a critical dimension of 0.75 m (2.46 ft.) or a vehicle, typically defined with a critical dimension of 2.3 m (7.55 ft.). Johnson measured the ability of observers to identify scale model targets under various conditions, and came up with criteria for the minimum required resolution. These criteria provide a 50 % probability of an observer distinguishing an object at the specified level. For a thermal sensor, the temperature difference between the object and its background needs to be at least 2 °C. The levels of Johnson's criteria used for Axis thermal network cameras are as follows: 4