Abstract
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.
Highlights
Automatic target recognition (ATR) is an important and challenging problem for a wide range of military and civilian applications
Since forward-looking infrared (FLIR) images are frequently used in ATR applications, many algorithms have been proposed in FLIR imagery in recent years [1], such as learning-based [2,3] and model-based [4,5,6,7,8,9] methods
In [36], Zhu et al proposed the orthogonal combination of local binary patterns (OC_LBP), which drastically reduces the dimensionality of the original LBP histogram to 4 × P by combining the histograms of [P/4]different four-orthogonal neighbor operators
Summary
Automatic target recognition (ATR) is an important and challenging problem for a wide range of military and civilian applications. We focus on local binary pattern (LBP), a simple yet effective approach, for infrared ATR. It has achieved promising results in several ATR applications in recent years, such as maritime target detection and recognition in [19], infrared building recognition in [20], ISAR-based ATR in [21] and infrared ATR in our previous work [22]. Based on RLTP, SCCP and OC_LBP, a novel operator is introduced in the paper, which is named the soft concave-convex orthogonal combination of robust local ternary patterns (SCC_OC_RLTP).
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
