Future Work

During the course of this quarter, we have generated several different experiments acquiring the histogram and ROC for the database. In future, we will be collecting more finger prints under the water aged conditions as more images will result in more concrete results. To acquire more data, especially with water aged finger prints, we may recruit students in swim team to contribute prints of their pruney fingers to our dataset.

Result & Conclusion

Upon running the algorithm on the entire data set, including both wet and dry finger prints, we achieved our initial results. As the ROC curve and histogram plot indicate, the algorithm does really well under the factors of water aging.


ROC curve of genuine vesus imposture match scores
There is a clear distinction between the scores of genuine versus those of the impostors. The ROC curve for the result also indicates that minutiae based algorithms overcomes the factor of water aging.


Histogram plot of genuine versus imposture match scores
Our next tests were with two separate data sets, one of which is just dry prints, and the other just wet prints. The histograms for these two experiments confirms our hypothesis that water aging does not significantly impact the performance of minutiae based algorithms.


Histogram of Genuine vs. Impostor scores for both dry and wet prints
In the test trial with just wet prints, we were assuming to see some variation in the impostor and genuine scores, believing that the image quality of the wet prints is not as good as those of the dry prints. However, the histogram plot in figure 6 indicates that the different quality did not deter the algorithm from matching the minutiae. Thus our initial hypothesis is confirmed with the results we achieved.