Palmprint Image Quality Measures in Minutiae-based Recognition

The performance of a minutiae-based palmprint recognition system relies heavily on the quality´ of captured palmprint images. This paper introduces a block-based approach to evaluate the quality of a palmprint, in which two inter-block indices and four inner-block indices are developed. Inter-block quality indices includes block level orientation continuity, ridge thickness uniformity, while inner-block quality indices involve smudginess dryness judgment, the certainty of orientation in a block, ridge-valley frequency value, and special regions information. The final block quality value and image quality value arc calculated based on these six indices. In experiment part, we evaluate the proposed measurement from three aspects: by comparing with human visual inspection, by observing the rise of Accuracy Rate after masking and by watching the relationship between GI value and final image quality value Q. These results show that our measurement can predict the quality of palmprint images accurately.