The fringe-adjusted joint transform correlation (FJTC) technique has been widely used for real-time optical
pattern recognition applications. However, the classical FJTC technique suffers from target distortions due to
noise, scale, rotation and illumination variations of the targets in input scenes. Several improvements of the
FJTC have been proposed in the literature to accommodate these problems. Some popular techniques such as
synthetic discriminant function (SDF) based FJTC was designed to alleviate the problems of scale and rotation
variations of the target, whereas wavelet based FJTC has been found to yield better performance for noisy
targets in the input scenes. While these techniques integrated with specific features to improve performance of
the FJTC, a unified and synergistic approach to equip the FJTC with robust features is yet to be done. Thus, in
this paper, a robust FJTC technique based on sequential filtering approach is proposed. The proposed method
is developed in such a way that it is insensitive to rotation, scale, noise and illumination variations of the targets.
Specifically, local phase (LP) features from monogenic signal is utilized to reduce the effect of background
illumination thereby achieving illumination invariance. The SDF is implemented to achieve rotation and scale
invariance, whereas the logarithmic fringe-adjusted filter (LFAF) is employed to reduce the noise effect. The
proposed technique can be used as a real-time region-of-interest detector in wide-area surveillance for automatic
object detection. The feasibility of the proposed technique has been tested on aerial imagery and has observed
promising performance in detection accuracy.