Low-Light Image Object Detection Based on Improved YOLOv5 Algorithm

Ziting Shu; Zebin Zhang; Yaozhe Song; Mengmeng Wu; Xiaobing Yuan

doi:10.3788/LOP212965

Laser & Optoelectronics Progress, Volume. 60, Issue 4, 0404001(2023)

Low-Light Image Object Detection Based on Improved YOLOv5 Algorithm

Ziting Shu^1,2, Zebin Zhang^1,2, Yaozhe Song^1,2, Mengmeng Wu^1,2, and Xiaobing Yuan^1、*

¹Key Laboratory of Microsystem Technology, Shanghai Institute of Microsystem and Information Technology, Chinese Academy of Sciences, Shanghai 201800, China

²University of Chinese Academy of Sciences, Beijing 100049, China

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Figures & Tables(12)

Fig. 1. YOLOv5 network structure

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Fig. 2. Low-light image and enhanced images. (a) ExDark dataset; (b) LIME; (c) EnlightenGAN; (d) DEC_ZERO

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Fig. 3. Feature visualization results of low-light images and enhanced images

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Fig. 4. Feature enhancement module based on channel attention mechanism

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Fig. 5. Feature location module

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Fig. 6. YOLOv5_DC overall network structure

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Fig. 7. Normal illumination image and synthetic low-light image. (a) Normal illumination image; (b) synthetic low-light image

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Table 1. Detection results of different datasets
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Table 1. Detection results of different datasets
Dataset mAP@0.5∶0.95 mAP@0.5
Dataset obtained by LIME 0.3758 0.6406
Dataset obtained by EnlightenGAN 0.3897 0.6577
Dataset obtained by DCE_ZERO 0.3915 0.6620
ExDark 0.3941 0.6605

Table 2. Performance comparison of different object detection algorithms on ExDark dataset

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Table 2. Performance comparison of different object detection algorithms on ExDark dataset

Algorithm	mAP@0.5∶0.95	mAP@0.5
YOLOv5	0.3941	0.6605
LIME+YOLOv5	0.3758	0.6406
DCE_ZERO+YOLOv5	0.3915	0.6620
EnlightenGAN+YOLOv5	0.3897	0.6577
RFB-Dark^［6］	0.3530	0.6550
CycleGAN-ResNet^［10］	0.3240
LIME+YOLOv5_DC（ours）	0.4126	0.6934
DCE_ZERO+YOLOv5_DC（ours）	0.4152	0.6946
EnlightenGAN+YOLOv5_DC（ours）	0.4162	0.6972

Table 3. Performance comparison of different object detection algorithms on ExDark^* dataset

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Table 3. Performance comparison of different object detection algorithms on ExDark^* dataset

Detection algorithm	Image size	mAP@0.5∶0.95	mAP@0.5
Faster RCNN	600×1000	0.2491	0.5438
DCE_ZERO + Faster RCNN	600×1000	0.2527	0.5453
EnlightenGAN + Faster RCNN	600×1000	0.2456	0.5322
RFB-Net	300	0.3651	0.6484
DCE_ZERO + RFB-Net	300	0.3455	0.6201
EnlightenGAN + RFB-Net	300	0.3275	0.5941
YOLOv5	640	0.4260	0.7057
DCE_ZERO + YOLOv5	640	0.4240	0.7029
EnlightenGAN + YOLOv5	640	0.4237	0.7011
DCE_ZERO + YOLOv5_DC（ours）	640	0.4301	0.7176
EnlightenGAN + YOLOv5_DC（ours）	640	0.4354	0.7185

Table 4. Detection performance of YOLOv5_DC under different input conditions
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Table 4. Detection performance of YOLOv5_DC under different input conditions
Input Dataset mAP@0.5∶0.95 mAP@0.5
low-light image+low-light image ExDark^* 0.4248 0.7077
low-light image+DCE_ZERO ExDark^* 0.4301 0.7176
low-light image+EnlightenGAN ExDark^* 0.4354 0.7185

Table 5. Results of ablation experimental on ExDark^* dataset
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Table 5. Results of ablation experimental on ExDark^* dataset
FE_CBM FL module mAP@0.5∶0.95 mAP@0.5
0.4237 0.7011
√ 0.4306 0.7120
√ √ 0.4351 0.7185

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Ziting Shu, Zebin Zhang, Yaozhe Song, Mengmeng Wu, Xiaobing Yuan. Low-Light Image Object Detection Based on Improved YOLOv5 Algorithm[J]. Laser & Optoelectronics Progress, 2023, 60(4): 0404001

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Paper Information

Category: Detectors

Received: Nov. 16, 2021

Accepted: Dec. 24, 2021

Published Online: Feb. 14, 2023

The Author Email: Yuan Xiaobing (yuanxb@mail.sim.ac.cn)

DOI:10.3788/LOP212965

Topics

laser devices and laser physics

Lasers and Laser Optics

Laser physics

laser manufacturing

Instrumentation, Measurement and Metrology

Table 1. Detection results of different datasets

Table 1. Detection results of different datasets

Table 2. Performance comparison of different object detection algorithms on ExDark dataset

Table 2. Performance comparison of different object detection algorithms on ExDark dataset

Table 3. Performance comparison of different object detection algorithms on ExDark* dataset

Table 3. Performance comparison of different object detection algorithms on ExDark* dataset

Table 4. Detection performance of YOLOv5_DC under different input conditions

Table 4. Detection performance of YOLOv5_DC under different input conditions

Table 5. Results of ablation experimental on ExDark* dataset

Table 5. Results of ablation experimental on ExDark* dataset

Table 3. Performance comparison of different object detection algorithms on ExDark^* dataset

Table 3. Performance comparison of different object detection algorithms on ExDark^* dataset

Table 5. Results of ablation experimental on ExDark^* dataset

Table 5. Results of ablation experimental on ExDark^* dataset