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Score level fusion in multi-biometric identification based on zones of interest - ScienceDirect
Source: sciencedirect.com
Article summary:
1. This paper presents a new multibiometric fusion method for the identification of persons using two modalities, the iris and the fingerprint.
2. The fusion is applied at the score level, with a preliminary study based on k-means clustering to split the score range into three zones of interest relevant to the proposed identification method.
3. Two approaches are used for fusion: one based on decision tree combined with weighted sum (BCC) and another based on fuzzy logic (BFL).
Article analysis:
This article provides an overview of a new multibiometric fusion method for person identification using two modalities, namely iris and fingerprint. The authors present two approaches for score level fusion, namely BCC and BFL, which are evaluated on standard biometric databases using four metrics. The results obtained from these tests show that the proposed methods outperform those based on single modality and that BCC achieves slightly better performance than BFL.
The article is generally well written and provides sufficient detail about the proposed methods as well as their evaluation results. However, there are some points that could be improved upon in terms of trustworthiness and reliability. For example, while the authors provide details about their evaluation metrics, they do not provide any information about how these metrics were chosen or why they were considered appropriate for this particular application. Additionally, while the authors mention possible risks associated with their approach, they do not provide any details about how these risks can be mitigated or avoided. Furthermore, while the authors discuss potential applications of their approach in other domains such as image processing, they do not provide any evidence to support this claim or explore any counterarguments that may exist against it. Finally, while the authors discuss potential improvements to their approach in future work, they do not provide any concrete suggestions or ideas on how this could be achieved.
In conclusion, while this article provides an interesting overview of a new multibiometric fusion method for person identification using two modalities, there are some areas where its trustworthiness and reliability could be improved upon by providing more detailed information about certain aspects such as evaluation metrics and potential risks associated with its use as well as exploring counterarguments against potential applications in other domains.