Evaluating Feature-Based Homography Pipelines for Dual-Camera Registration in Acupoint Annotation Article Swipe
Thathsara Nanayakkara
,
Hadi Sedigh Malekroodi
,
Jae-Uk Sul
,
Chang-Su Na
,
Myunggi Yi
,
Byeong-Il Lee
·
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.3390/jimaging11110388
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.3390/jimaging11110388
Reliable acupoint localization is essential for developing artificial intelligence (AI) and extended reality (XR) tools in traditional Korean medicine; however, conventional annotation of 2D images often suffers from inter- and intra-annotator variability. This study presents a low-cost dual-camera imaging system that fuses infrared (IR) and RGB views on a Raspberry Pi 5 platform, incorporating an IR ink pen in conjunction with a 780 nm emitter array to standardize point visibility. Among the tested marking materials, the IR ink showed the highest contrast and visibility under IR illumination, making it the most suitable for acupoint detection. Five feature detectors (SIFT, ORB, KAZE, AKAZE, and BRISK) were evaluated with two matchers (FLANN and BF) to construct representative homography pipelines. Comparative evaluations across multiple camera-to-surface distances revealed that KAZE + FLANN achieved the lowest mean 2D error (1.17 ± 0.70 px) and the lowest mean aspect-aware error (0.08 ± 0.05%) while remaining computationally feasible on the Raspberry Pi 5. In hand-image experiments across multiple postures, the dual-camera registration maintained a mean 2D error below ~3 px and a mean aspect-aware error below ~0.25%, confirming stable and reproducible performance. The proposed framework provides a practical foundation for generating high-quality acupoint datasets, supporting future AI-based localization, XR integration, and automated acupuncture-education systems.
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- Type
- article
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- en
- Landing Page
- https://doi.org/10.3390/jimaging11110388
- https://www.mdpi.com/2313-433X/11/11/388/pdf?version=1762002835
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- 33
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Evaluating Feature-Based Homography Pipelines for Dual-Camera Registration in Acupoint AnnotationWork title
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articleOpenAlex work type
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enPrimary language
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2025Year of publication
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2025-11-01Full publication date if available
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Thathsara Nanayakkara, Hadi Sedigh Malekroodi, Jae-Uk Sul, Chang-Su Na, Myunggi Yi, Byeong-Il LeeList of authors in order
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https://doi.org/10.3390/jimaging11110388Publisher landing page
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https://www.mdpi.com/2313-433X/11/11/388/pdf?version=1762002835Direct link to full text PDF
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YesWhether a free full text is available
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goldOpen access status per OpenAlex
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https://www.mdpi.com/2313-433X/11/11/388/pdf?version=1762002835Direct OA link when available
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0Total citation count in OpenAlex
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33Number of works referenced by this work
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| abstract_inverted_index.matchers | 108 |
| abstract_inverted_index.multiple | 120, 160 |
| abstract_inverted_index.presents | 34 |
| abstract_inverted_index.proposed | 186 |
| abstract_inverted_index.provides | 188 |
| abstract_inverted_index.revealed | 123 |
| abstract_inverted_index.suitable | 91 |
| abstract_inverted_index.systems. | 206 |
| abstract_inverted_index.Raspberry | 49, 153 |
| abstract_inverted_index.automated | 204 |
| abstract_inverted_index.construct | 113 |
| abstract_inverted_index.datasets, | 196 |
| abstract_inverted_index.detectors | 97 |
| abstract_inverted_index.distances | 122 |
| abstract_inverted_index.essential | 4 |
| abstract_inverted_index.evaluated | 105 |
| abstract_inverted_index.framework | 187 |
| abstract_inverted_index.medicine; | 18 |
| abstract_inverted_index.platform, | 52 |
| abstract_inverted_index.postures, | 161 |
| abstract_inverted_index.practical | 190 |
| abstract_inverted_index.remaining | 148 |
| abstract_inverted_index.annotation | 21 |
| abstract_inverted_index.artificial | 7 |
| abstract_inverted_index.confirming | 180 |
| abstract_inverted_index.detection. | 94 |
| abstract_inverted_index.developing | 6 |
| abstract_inverted_index.foundation | 191 |
| abstract_inverted_index.generating | 193 |
| abstract_inverted_index.hand-image | 157 |
| abstract_inverted_index.homography | 115 |
| abstract_inverted_index.maintained | 165 |
| abstract_inverted_index.materials, | 74 |
| abstract_inverted_index.pipelines. | 116 |
| abstract_inverted_index.supporting | 197 |
| abstract_inverted_index.visibility | 83 |
| abstract_inverted_index.Comparative | 117 |
| abstract_inverted_index.conjunction | 59 |
| abstract_inverted_index.dual-camera | 37, 163 |
| abstract_inverted_index.evaluations | 118 |
| abstract_inverted_index.experiments | 158 |
| abstract_inverted_index.standardize | 67 |
| abstract_inverted_index.traditional | 16 |
| abstract_inverted_index.visibility. | 69 |
| abstract_inverted_index.aspect-aware | 142, 176 |
| abstract_inverted_index.conventional | 20 |
| abstract_inverted_index.high-quality | 194 |
| abstract_inverted_index.integration, | 202 |
| abstract_inverted_index.intelligence | 8 |
| abstract_inverted_index.localization | 2 |
| abstract_inverted_index.performance. | 184 |
| abstract_inverted_index.registration | 164 |
| abstract_inverted_index.reproducible | 183 |
| abstract_inverted_index.variability. | 31 |
| abstract_inverted_index.illumination, | 86 |
| abstract_inverted_index.incorporating | 53 |
| abstract_inverted_index.localization, | 200 |
| abstract_inverted_index.representative | 114 |
| abstract_inverted_index.computationally | 149 |
| abstract_inverted_index.intra-annotator | 30 |
| abstract_inverted_index.camera-to-surface | 121 |
| abstract_inverted_index.acupuncture-education | 205 |
| cited_by_percentile_year | |
| corresponding_author_ids | https://openalex.org/A5035582621, https://openalex.org/A5010623403 |
| countries_distinct_count | 1 |
| institutions_distinct_count | 6 |
| corresponding_institution_ids | https://openalex.org/I8991828 |
| citation_normalized_percentile |