The Polar Mellin Transform (PMT) is a well-known technique that converts images into shift, scale and rotation invariant signatures for object detection using opto-electronic correlators. However, this technique cannot be properly applied when there are multiple targets in a single input. Here, we propose a Segmented PMT (SPMT) that extends this methodology for cases where multiple objects are present within the same frame. Simulations show that this SPMT can be integrated into an opto-electronic joint transform correlator to create a correlation system capable of detecting multiple objects simultaneously, presenting robust detection capabilities across various transformation conditions, with remarkable discrimination between matching and non-matching targets.
@article{arxiv.2503.14034,
title = {Shift, Scale and Rotation Invariant Multiple Object Detection using Balanced Joint Transform Correlator},
author = {Xi Shen and Julian Gamboa and Tabassom Hamidfar and Shamima Mitu and Selim M. Shahriar},
journal= {arXiv preprint arXiv:2503.14034},
year = {2025}
}