Fingerprint Feature Extraction by Combining Texture, Minutiae, and Frequency Spectrum Using Multi-Task CNN is a research study created by Ai Takahashi, Yoshinori Koda, Koichi Ito, and Takafumi Aoki.<u> For the purpose of extracting fingerprint features from texture, details, and frequency spectrum</u>, they offer a novel CNN-based method.
It was published on August 27, 2020. Their publisher is the Institute of Electrical and Electronics Engineers Inc. The authors of the novel CNN-based method research believe that the frequency spectrum is a useful feature because a fingerprint is made up of ridge patterns, each of which has its own inherent frequency band, even though the majority of fingerprint matching methods use minutiae points and/or combining texture of fingerprint images as fingerprint features.
They proved that their proposed method exhibits the efficient performance on fingerprint verification when compared with a commercial fingerprint matching program and the traditional method.
Learn about the steps for creating a genetic fingerprint in the correct order: brainly.com/question/28062812
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