article · 2019 International Russian Automation Conference (RusAutoCon) · 2019

Novel Method of Singularity Recognition of Fingerprints

Cited by 0Abstract and details only

Abstract

The authors introduce a quick technique based on the singular points for classifying fingerprints. The method detect singular points as (delta and core points), in fingerprints that are obtained from the orientation field. The technique improves the digitized image applying adaptive clustering, image processing, building the flow map by checking the orientations of individual pixels, computes histogram of flow map using overlapping blocks, and recognizing whorl, loop and deltas. The complexity of the technique is on the order of the number of pixels in the fingerprint image. The technique requires iterations without human feedback, and is highly parallel. In this the article, we proposed a new approach to recognize singularity, using cluster method and petal method.

Cite this paper

APA 7

Alanssari, A. (2019). Novel Method of Singularity Recognition of Fingerprints. 2019 International Russian Automation Conference (RusAutoCon), 5, 1–5. https://doi.org/10.1109/rusautocon.2019.8867667

MLA 9

Alanssari, A.N. “Novel Method of Singularity Recognition of Fingerprints.” 2019 International Russian Automation Conference (RusAutoCon), vol. 5, 2019, pp. 1–5, https://doi.org/10.1109/rusautocon.2019.8867667.

Chicago

Alanssari, A.N. 2019. “Novel Method of Singularity Recognition of Fingerprints.” 2019 International Russian Automation Conference (RusAutoCon) 5: 1–5. https://doi.org/10.1109/rusautocon.2019.8867667.

Harvard

Alanssari, A. (2019) ‘Novel Method of Singularity Recognition of Fingerprints’, 2019 International Russian Automation Conference (RusAutoCon), 5, pp. 1–5. Available at: https://doi.org/10.1109/rusautocon.2019.8867667.

BibTeX

@article{alanssari2019novel,
  title = {{Novel Method of Singularity Recognition of Fingerprints}},
  author = {Alanssari, A.N.},
  journal = {2019 International Russian Automation Conference (RusAutoCon)},
  volume = {5},
  pages = {1--5},
  year = {2019},
  doi = {10.1109/rusautocon.2019.8867667}
}

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