Data Fusion and Confidence Measure in Image Feature Detection

The data fusion approaches for uncorrelated and correlated data are carried out in image feature detection, which integrate information of the same feature based on multiple methods using a statistical approach. Validity of the scheme and properties of the fused data are discussed. A confidence measure is defined, and applied to evaluate credibility of the result. The technique can be used to reduce adverse effects of individual feature detection errors, and improve the rate of pattern recognition. Examples of facial canthus detection and the corresponding confidence levels are presented.