# Shift, Scale and Rotation Invariant Multiple Object Detection using Balanced Joint Transform Correlator

Source: [Shift, Scale and Rotation Invariant Multiple Object Detection using Balanced Joint Transform Correlator](<https://www.sota2.com/research/paper/68fa77801e209131cea73a18>)

Collection index: [llms.txt](<https://www.sota2.com/research/llms.txt>)

Data updated: 2025-10-26T04:20:40.032Z

Authors: Xi Shen, Julian Gamboa, Tabassom Hamidfar, Shamima Mitu, Selim M. Shahriar

Published: 2025-03-18T08:51:20.000Z

## Abstract

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.

## Recorded benchmark results

A research result applies to its stated dataset, split, metric and evaluation configuration. Compare like-for-like settings, preserve the metric's unit and direction, and distinguish paper-reported results from independent reproduction. The best result recorded here is not a claim of exhaustive, current global coverage.

## Original sources and implementation

[Original paper](<https://arxiv.org/abs/2503.14034>)

[PDF](<https://arxiv.org/pdf/2503.14034.pdf>)