Wavelet-modified segmented phase-only filter for in-plane rotated object recognition

Abstract

In this paper, we propose and implement a wavelet-modified segmented phase-only filter for in-plane rotated object recognition. The wavelet filter is combined with the segmented phase-only filter to significantly enhance the correlation capability of the optical processor. To verify the consistency of the results, we have calculated the performance measure parameters such as peak-to-correlation energy, peak-to-sidelobe ratio, discrimination ratio and signal-to-noise ratio and compared the performance with a conventional segmented phase-only filter. For carrying out the study, we have developed a dataset of different distorted objects such as alphabets, digits, vehicles, fighter planes. Through a series of experiments and case studies, we are able to prove that the proposed filter reduces the false alarm rate while increasing recognition capability.