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| Autori principali: | , , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2025
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| Soggetti: | |
| Accesso online: | https://arxiv.org/abs/2503.14034 |
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| _version_ | 1866910880534364160 |
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| author | Shen, Xi Gamboa, Julian Hamidfar, Tabassom Mitu, Shamima Shahriar, Selim M. |
| author_facet | Shen, Xi Gamboa, Julian Hamidfar, Tabassom Mitu, Shamima Shahriar, Selim M. |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2503_14034 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Shift, Scale and Rotation Invariant Multiple Object Detection using Balanced Joint Transform Correlator Shen, Xi Gamboa, Julian Hamidfar, Tabassom Mitu, Shamima Shahriar, Selim M. Image and Video Processing Computer Vision and Pattern Recognition 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. |
| title | Shift, Scale and Rotation Invariant Multiple Object Detection using Balanced Joint Transform Correlator |
| topic | Image and Video Processing Computer Vision and Pattern Recognition |
| url | https://arxiv.org/abs/2503.14034 |