Improved Local Ternary Patterns for Automatic Target Recognition in Infrared Imagery

This paper presents an improved local ternary pattern (LTP) for automatic target recognition (ATR) in infrared imagery. Firstly, a robust LTP (RLTP) scheme is proposed to overcome the limitation of the original LTP for achieving the invariance with respect to the illumination transformation. Then, a soft concave-convex partition (SCCP) is introduced to add some flexibility to the original concave-convex partition (CCP) scheme. Referring to the orthogonal combination of local binary patterns (OC_LBP), the orthogonal combination of LTP (OC_LTP) is adopted to reduce the dimensionality of the LTP histogram. Further, a novel operator, called the soft concave-convex orthogonal combination of robust LTP (SCC_OC_RLTP), is proposed by combing RLTP, SCCP and OC_LTP Finally, the new operator is used for ATR along with a blocking schedule to improve its discriminability and a feature selection technique to enhance its efficiency Experimental results on infrared imagery show that the proposed features can achieve competitive ATR results compared with the state-of-the-art methods.

• Publication year

  2015

• Venue

  Italian National Conference on Sensors

• Publication date

  2015-03-01

• Fields of study

  Medicine, Computer Science, Engineering, Environmental Science

• Identifiers
  DOI 10.3390/s150306399PMID 25785311PMCID 4435149
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar, PubMed

• No claims are published for this paper.

• No concepts are published for this paper.

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