MCIR-YOLO:利用多波段红外图像进行白色药丸分类

IF 2.1 4区 工程技术 Q3 ENGINEERING, ELECTRICAL & ELECTRONIC IEEE Photonics Journal Pub Date : 2024-07-11 DOI:10.1109/JPHOT.2024.3426929
Mohan Wang;Yang Jiang;Baohui Xu;Mengqiang Huang;Xu Xue;Xu Wu;Wenjian Kuang;Xiang Liu;Harm Tolner
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引用次数: 0

摘要

药片的识别和分类是当代医院的关键任务,尤其是在避免用药错误方面。传统的视觉识别和分类方法主要依赖于可见光图像,不足以辨别具有相似视觉特征的白色药片。然而,白色药丸在各种光谱波段上都表现出与众不同的红外特性。基于这些观察结果,本文介绍了 MCIR-YOLO 算法,这是一种多波段红外图像目标检测系统,通过多模态融合技术增强了 YOLOv5s 模型。本研究提出了一个新颖的数据集,该数据集由六个波段的白色圆形药丸红外图像组成,峰值波长范围约为 1400 nm 到 1650 nm。此外,还提出了一种多模态融合策略,促进了六个红外通道的多层次特征整合。这种融合技术利用了每种红外模式固有的尺度特征,从而实现了多种模式的综合信息融合。此外,该模型还包含一个独立于主干网的辅助检测分支,它利用融合的特征信息来计算不同的损失,从而有效地减少整体损失。注意机制模块集成在两个不同的融合点之后,以提高特征精度。利用红外特征的均值和缩放,这些注意机制显著提高了检测精度。实验结果表明,改进后的模型优于基线 YOLOv5s 模型,这一点在自建的白色圆丸红外图像数据集中尤为明显,单通道(峰值为 1650 nm)和六通道配置的 mAP0.5 分别提高了 5.47% 和 7.96%。值得注意的是,利用 MCIR-YOLO 模型进行六通道识别比性能最佳的单通道红外图像识别有 12.05% 的显著优势。
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MCIR-YOLO: White Medication Pill Classification Using Multi-Band Infrared Images
The identification and categorization of pills constitute critical tasks within a contemporary hospital, particularly for avoiding medication errors. Conventional approaches to visual recognition and classification predominantly rely on visible light imagery, proving inadequate for discerning white pills with similar visual characteristics. However, white pills exhibit distinctive infrared properties across various spectral bands. Building upon these observations, this paper introduces the MCIR-YOLO algorithm, a multi-band infrared image object detection system, which enhances the YOLOv5s model through multimodal fusion techniques. This study presents a novel dataset comprising IR images of white round pills captured across six channels, with peak wavelengths ranging from approximately 1400 nm to 1650 nm. Furthermore, a multimodal fusion strategy is proposed, facilitating multi-level feature integration across the six IR channels. This fusion technique exploits the scale features inherent to each IR modality, thereby enabling comprehensive information fusion across multiple modalities. Additionally, the model incorporates an auxiliary detection branch, independent of the backbone, which utilizes fused feature information to calculate a distinct loss, effectively mitigating overall loss. Attention mechanism modules are integrated after two distinct fusion points to enhance feature precision. Leveraging mean and scaling of IR features, these attention mechanisms significantly boost detection accuracy. Experimental results demonstrate that the improved model outperforms the baseline YOLOv5s model, particularly evident in a self-constructed dataset of white round pill IR images, where mAP0.5 increased by 5.47% and 7.96% for single-channel (peak at 1650 nm) and six-channel configurations, respectively. Notably, the utilization of the MCIR-YOLO model for six-channel recognition yields a substantial advantage of 12.05% over the best-performing single-channel IR image recognition.
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来源期刊
IEEE Photonics Journal
IEEE Photonics Journal ENGINEERING, ELECTRICAL & ELECTRONIC-OPTICS
CiteScore
4.50
自引率
8.30%
发文量
489
审稿时长
1.4 months
期刊介绍: Breakthroughs in the generation of light and in its control and utilization have given rise to the field of Photonics, a rapidly expanding area of science and technology with major technological and economic impact. Photonics integrates quantum electronics and optics to accelerate progress in the generation of novel photon sources and in their utilization in emerging applications at the micro and nano scales spanning from the far-infrared/THz to the x-ray region of the electromagnetic spectrum. IEEE Photonics Journal is an online-only journal dedicated to the rapid disclosure of top-quality peer-reviewed research at the forefront of all areas of photonics. Contributions addressing issues ranging from fundamental understanding to emerging technologies and applications are within the scope of the Journal. The Journal includes topics in: Photon sources from far infrared to X-rays, Photonics materials and engineered photonic structures, Integrated optics and optoelectronic, Ultrafast, attosecond, high field and short wavelength photonics, Biophotonics, including DNA photonics, Nanophotonics, Magnetophotonics, Fundamentals of light propagation and interaction; nonlinear effects, Optical data storage, Fiber optics and optical communications devices, systems, and technologies, Micro Opto Electro Mechanical Systems (MOEMS), Microwave photonics, Optical Sensors.
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