MGT-Fusion: PCBA Defect Detection Method Based on Texture and Depth Information Fusion (Invited)

Zefang Chen; Mingyuan Zhong; Hailong Jing; Guodong Liu; Qican Zhang; Junfei Shen

doi:10.3788/LOP251144

Laser & Optoelectronics Progress, Volume. 62, Issue 17, 1739022(2025)

MGT-Fusion: PCBA Defect Detection Method Based on Texture and Depth Information Fusion (Invited)

Zefang Chen¹, Mingyuan Zhong¹, Hailong Jing², Guodong Liu³, Qican Zhang^1、*, and Junfei Shen^1、**

Author Affiliations

¹College of Electronics and Information Engineering, Sichuan University, Chengdu 610065, Sichuan , China

²Sichuan ViSensing Technology Co., Ltd., Chengdu 610065, Sichuan , China

³United Electronics Co., Ltd., Jiangxi, Nanchang 330000, Jiangxi , China

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Figures & Tables(9)

Fig. 1. Structure of MGT-Fusion network

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Fig. 2. Structure of GFM

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Fig. 3. Structure of TFM

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Fig. 4. Images of the data acquisition setup. (a) Real picture; (b) 3D structure diagram

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Fig. 5. Schematic diagrams of each defect type contained in PCBA dataset

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Fig. 6. Qualitative comparison of detection effects by different methods

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Table 1. Comparison of detection results by different methods on the PCBA defect dataset

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Table 1. Comparison of detection results by different methods on the PCBA defect dataset

Method	Type of input image	Params /10⁶	mAP50 /%	F1_Score /%	FPS /Hz
DETR	RGB image	36.7	95.34	92	9.41
DETR	Depth image	36.7	90.63	89	9.17
YOLOv7-l	RGB image	28.5	96.05	93	11.28
YOLOv7-l	Depth image	28.5	91.19	90	11.09
YOLOv8-m	RGB image	25.9	96.82	94	12.13
YOLOv8-m	Depth image	25.9	92.55	91	12.07
YOLOv12-m	RGB image	19.5	97.12	94	29.42
YOLOv12-m	Depth image	19.5	92.77	91	29.76
RT-DETR	RGB image	32.8	97.56	96	22.67
RT-DETR	Depth image	32.8	93.05	92	23.64
MGT-Fusion	RGB image+depth image	43.6	99.89	99	7.51

Table 2. Comparison of APs for different types of defects detection by different methods

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Table 2. Comparison of APs for different types of defects detection by different methods

Method	Type ofinput image	Missingpart	Dimension wrong	Part tilt	Part shift	Side termination	Upturned	Insufficient solder	Bridge	Pin offset
DETR	RGB image	92.80	97.22	93.91	91.74	90.43	95.88	99.54	99.36	97.21
DETR	Depth image	81.37	96.27	96.91	97.53	97.33	62.13	99.31	97.10	87.73
YOLOv7-l	RGB image	93.33	97.65	95.61	94.49	93.88	95.04	99.05	98.52	96.89
YOLOv7-l	Depth image	83.47	96.29	97.29	97.41	96.99	63.83	97.79	98.37	89.33
YOLOv8-m	RGB image	96.19	97.75	98.42	97.93	93.64	95.76	98.03	96.56	97.17
YOLOv8-m	Depth image	79.98	93.97	97.65	97.29	98.07	79.21	98.11	99.00	89.69
YOLOv12-m	RGB image	95.51	98.46	96.07	96.35	94.63	95.69	99.47	99.53	97.11
YOLOv12-m	Depth image	84.13	97.43	97.91	98.12	98.84	71.05	99.51	99.52	90.56
RT-DETR	RGB image	95.86	98.78	98.45	97.31	95.24	96.82	99.47	99.57	97.46
RT-DETR	Depth image	84.01	94.35	98.38	98.86	99.19	72.47	98.65	99.46	91.49
MGT-Fusion	RGB image+depth image	100.00	100.00	99.81	99.99	99.63	100.00	99.99	99.63	99.94

Table 3. Results of ablation experiments
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Table 3. Results of ablation experiments
T P TFM GFM Params /10⁶ mAP50 /% F1_Score /%
√ 21.10 94.43 94
√ 21.10 89.73 89
√ √ 33.49 98.72 98
√ √ √ 40.47 99.46 99
√ √ √ √ 43.63 99.89 99

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Zefang Chen, Mingyuan Zhong, Hailong Jing, Guodong Liu, Qican Zhang, Junfei Shen. MGT-Fusion: PCBA Defect Detection Method Based on Texture and Depth Information Fusion (Invited)[J]. Laser & Optoelectronics Progress, 2025, 62(17): 1739022

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Paper Information

Category: AI for Optics

Received: May. 4, 2025

Accepted: Jun. 30, 2025

Published Online: Sep. 8, 2025

The Author Email: Qican Zhang (zqc@scu.edu.cn), Junfei Shen (shenjunfei@scu.edu.cn)

DOI:10.3788/LOP251144

CSTR:32186.14.LOP251144

Topics

laser devices and laser physics

Lasers and Laser Optics

Laser physics

laser manufacturing

Instrumentation, Measurement and Metrology

Table 1. Comparison of detection results by different methods on the PCBA defect dataset

Table 1. Comparison of detection results by different methods on the PCBA defect dataset

Table 2. Comparison of APs for different types of defects detection by different methods

Table 2. Comparison of APs for different types of defects detection by different methods

Table 3. Results of ablation experiments

Table 3. Results of ablation experiments