A binary based HMAX model for object recognition

Tae Koo Kang, Huazhen Zhang, Dong Sung Pae, Myo Taeg Lim

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In this paper, we propose a fast binary based HMAX model (B-HMAX). In our method, we detect corner based interest points after the second layer C1 to extract fewer numbers of features with better distinctiveness, and use binary string to describe the image patches extracted around detected corners, then use hamming distance for matching between two patches in the third layer S2, which is much faster than Euclidean method. Experimental results demonstrate that our proposed B-HMAX model can significantly reduce the total process time, while keeping the accuracy performance as the same with or better than standard HMAX.

Original languageEnglish
Title of host publicationICCAS 2015 - 2015 15th International Conference on Control, Automation and Systems, Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1297-1301
Number of pages5
ISBN (Print)9788993215090
DOIs
Publication statusPublished - 2015 Dec 23
Event15th International Conference on Control, Automation and Systems, ICCAS 2015 - Busan, Korea, Republic of
Duration: 2015 Oct 132015 Oct 16

Other

Other15th International Conference on Control, Automation and Systems, ICCAS 2015
CountryKorea, Republic of
CityBusan
Period15/10/1315/10/16

Keywords

  • Binary descriptor
  • Biologically inspired model
  • HMAX
  • Object recognition

ASJC Scopus subject areas

  • Control and Systems Engineering

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  • Cite this

    Kang, T. K., Zhang, H., Pae, D. S., & Lim, M. T. (2015). A binary based HMAX model for object recognition. In ICCAS 2015 - 2015 15th International Conference on Control, Automation and Systems, Proceedings (pp. 1297-1301). [7364837] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICCAS.2015.7364837