Selecting a composite correlation filter design: a survey and comparative study

Abstract

Many composite correlation filter designs have been proposed for solving a wide variety of target detection and pattern recognition problems. Due to the large number of available designs, however, it is often unclear how to select the best design for a particular application. We present a theoretical survey and an empirical comparison of several popular composite correlation filter designs. Using a database of rotational target imagery, we show that some such filter designs appear to be better choices than others under computational and performance constraints. We compare filter performance in terms of noise tolerance, computational load, generalization ability, and distortion in order to provide a multifaceted examination of the characteristics of various filter designs.

Automatic Target Recognition in Cluttered Visible Imagery

“…The field of correlation-filter-based pattern recognition (Kerekes and Kumar, 2008;Priyadarsini et al, 2012) has been researched extensively over the past three decades and successfully used in various applications. This success is largely due to attractive properties such as shift invariance, graceful degradation and closed-form solutions.…”

“…In contrast to simple matched filters, composite CF (Kerekes and Kumar, 2008) designs allow the use of multiple training images and can produce a filter template that tolerates different types of noise and distortion. Many such designs also optimize performance criteria such as peak sharpness, output similarity and low output noise variance for improved performance in various conditions.…”

“…Automatic Target Recognition (ATR) (Kerekes and Kumar, 2008;Priyadarsini et al, 2012) in cluttered imagery faces a large number of problems as there could be targets with varied sizes and presentations, the targets can be in low contrast and varied illumination locations. The images can have varied brightness and different gray level variations in real time scenarios, which forces us to design a very effective filter for detection of the target which can overcome all the obstacles.…”

Polynomial Correlation Filters for Human Face Recognition

“…Correlation filters are based on a closed form solution optimized to carefully construct performance figures of merit. Correlation filters [4] are inherently shift-invariant allowing us to apply them without any need to segment or register images prior to correlation.…”

Invariant correlation filter with linear phase coefficient holographic realization in 4-F correlator

“…Several approaches of CF design were proposed and investigated. 2, 3 We choose linear phase coefficient composite filter (LPCCF) which showed promising results of application to recognition of objects represented as binary edged images. 4,5 Realization of CF in optical correlators is of special interest due to the possibility of significant reduction in time required for input scene processing.…”