Human Detection and Tracking
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Habituated Subject A user of a biometric system who is well versed in its use; someone who routinely uses a biometric system. ▶ Iris on the Move
exposure to a device or process, the formal training that goes along with it, and individual learning and experimentation. The second characteristic, habituation consists of two parts, partially habituated and fully habituated. 1. Acclimation is the process in which a user of a biometric system adapts his or her techniques to achieve a proper match of his or her biometric template. 2. External Teaching is the formal training that a user receives revealing proper techniques and the series of steps included with using the biometric system. 3. Self teaching occurs after external teaching where a user experiments with the device and begins to eliminate techniques that do not work well or are not comfortable. Through this iterative process, techniques that work are narrowed, leading to partial habituation. 4. Partial habituation is defined as the period of time when no new adaptation of techniques is used to achieve a proper match to the biometric template. 5. Full or complete habituation is defined as the point at which a user matches his or her biometric template using subconscious techniques. ▶ Ergonomic Design for Biometric Systems
Halo Effect Habituation The academic and medical world has several different definitions for habituation. Two recurrent characteristics in the literature are acclimation and habituation. The first is acclimation, which consists of a user’s first
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2009 Springer Science+Business Media, LLC
The temperature difference between a wet finger and the platen of an optical sensor generates a halo on the final image around the fingerprint. ▶ Fingerprint, Palmprint, Handprint and Soleprint Sensor
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Hamming Distance
Hamming Distance A measurement of the (dis)similarity between two strings of bits having equal length, based on tallying how many corresponding pairs of bits in the two strings disagree. If each string has N bits, then a cardinal Hamming Distance is the count of disagreeing bits and is thus an integer between 0 and N inclusively. Alternatively, a fractional Hamming Distance normalizes (divides) this count by the total N and is thus a rational number between 0 and 1. Hamming Distance is an extremely fast metric to compute because it can be implemented digitally by simple Exclusive-OR logic operating in parallel on chunks of bits as large as the word length of the processor itself (e.g., 64 bits at once) in a single executable instruction cycle, and thus within almost a single ‘‘tick’’ of the system clock. In dedicated hardware there is no necessary limit to how many bits can be XOR’ed at once, thus allowing Hamming Distances to be computed at virtually unlimited rates. This confers an advantage to this similarity metric when searching databases on a national scale. A normalized Hamming Distance is the metric underlying the matching of IrisCodes for recognizing persons by their iris patterns. ▶ Iris Encoding and Recognition using Gabor
