Quality-based fusion refers to the use of quality measures in combining several biometric system outputs. Quality measures are an array of measurements quantifying the degree of excellence or conformance of biometric samples to some predefined criteria known to influence the system performance. Examples of quality measures for face biometrics are focus, contrast, and face detection reliability; and for iris biometrics are iris texture richness, the area of iris used for matching, and iris detection reliability. In quality-based fusion, the match scores of biometric samples of higher quality are considered more important, i.e., given higher weights, in order to compute the final combined score.
Quality-based fusion in the context of multibiometric systems is more challenging than multi-algorithmic systems because quality measures of the different biometric modalities are not comparable. This implies that quality-based fusion...
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