mlsanityData to 14 Oct 2026

Indexing Irises by Intrinsic Dimension

arXiv 2309.00705 ↗First posted 1 Sep 2023cs.CV eess.IVcited by 0

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Abstract (arXiv)

28,000+ high-quality iris images of 1350 distinct eyes from 650+ different individuals from a relatively diverse university town population were collected. A small defined unobstructed portion of the normalized iris image is selected as a key portion for quickly identifying an unknown individual when submitting an iris image to be matched to a database of enrolled irises of the 1350 distinct eyes. The intrinsic dimension of a set of these key portions of the 1350 enrolled irises is measured to be about four (4). This set is mapped to a four-dimensional intrinsic space by principal components analysis (PCA). When an iris image is presented to the iris database for identification, the search begins in the neighborhood of the location of its key portion in the 4D intrinsic space, typically finding a correct identifying match after comparison to only a few percent of the database.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 2 of its 23 references that are in the map. First posted on arXiv 1 Sep 2023.

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References · 2

  1. 2021Scikit-dimension: a Python package for intrinsic dimension estimationcited by 68
  2. 2019CC-Net: Image Complexity Guided Network Compression for Biomedical Image Segmentationcited by 13

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