Abstract

Near-regular texture (NRT), denoting deviations from otherwise symmetric wallpaper patterns, is commonly observable in the real world. Existing lattice detection algorithms capture the underlying lattice of an NRT pattern and all of its individual texels, facilitating an automated analysis of NRT. Many real world images, as in those of zebrafish larval histology arrays, depart significantly from regularity and challenge the current state of the art wallpaper group theory-based lattice detection methods. We propose an alternative 2D lattice detection algorithm that exploits translation and reflection symmetries and specific imaging cues. By outperforming existing methods on histology array images, our algorithm leads us towards complete automation of high-throughput histological image processing while broadening the spectrum of NRT computation.

Original languageEnglish (US)
Title of host publication2008 IEEE International Conference on Image Processing, ICIP 2008 Proceedings
Pages1452-1455
Number of pages4
DOIs
StatePublished - Dec 1 2008
Event2008 IEEE International Conference on Image Processing, ICIP 2008 - San Diego, CA, United States
Duration: Oct 12 2008Oct 15 2008

Publication series

NameProceedings - International Conference on Image Processing, ICIP
ISSN (Print)1522-4880

Other

Other2008 IEEE International Conference on Image Processing, ICIP 2008
CountryUnited States
CitySan Diego, CA
Period10/12/0810/15/08

All Science Journal Classification (ASJC) codes

  • Software
  • Computer Vision and Pattern Recognition
  • Signal Processing

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  • Cite this

    Canada, B. A., Thomas, G. K., Cheng, K., Wang, J., & Liu, Y. (2008). Automatic lattice detection in near-regular histology array images. In 2008 IEEE International Conference on Image Processing, ICIP 2008 Proceedings (pp. 1452-1455). [4712039] (Proceedings - International Conference on Image Processing, ICIP). https://doi.org/10.1109/ICIP.2008.4712039