Improved Lightweight Zero-Reference Deep Curve Estimation Low-Light Enhancement Algorithm for Night-Time Cow Detection
Abstract
:1. Introduction
2. Materials and Methods
2.1. Data Acquisition
2.2. Improved Lightweight Zero-DCE for Night-Time Cow Detection
2.2.1. Zero-DCE
2.2.2. Self-Attention Gate Mechanism
2.2.3. Kernel Selection Module
2.2.4. Depthwise Separable Convolution
- (1)
- Depthwise
- (2)
- Pointwise
2.2.5. ACT Module
2.2.6. Improved Lightweight Zero-DCE
2.3. Evaluation Indicators
3. Results and Analysis
3.1. Comparison of the Results of Different Models
3.2. Ablation Experiment
3.3. Detection Results before and after Day-Time Data Enhancement
4. Discussion
4.1. The Influence of Datasets on the Experimental Results
4.2. Performance Analysis of Improved Lightweight Zero-DCE
4.3. Possible Research Directions in the Future
5. Conclusions
Author Contributions
Funding
Data Availability Statement
Conflicts of Interest
References
- Khan, N. Critical Review of Dairy Cow Industry in the World. Food Chemistry eJournal. 2020. Available online: https://api.semanticscholar.org/CorpusID:219396510 (accessed on 23 June 2024).
- Wang, L.; Wu, T.; Zhang, Y.; Yang, K.; He, Y.; Deng, K.; Liang, C.; Gu, Y. Comparative studies on the nutritional and physicochemical properties of yoghurts from cows’, goats’, and camels’ milk powder. Int. Dairy J. 2023, 138, 105542. [Google Scholar] [CrossRef]
- Guo, Y.; Hong, W.; Wu, J.; Huang, X.; Qiao, Y.; Kong, H. Vision-Based Cow Tracking and Feeding Monitoring for Autonomous Livestock Farming: The YOLOv5s-CA+DeepSORT-Vision Transformer. IEEE Robot. Autom. Mag. 2023, 30, 68–76. [Google Scholar] [CrossRef]
- Han, S.; Fuentes, A.; Yoon, S.; Jeong, Y.; Kim, H.; Park, D.S. Deep learning-based multi-cattle tracking in crowded livestock farming using video. Comput. Electron. Agric. 2023, 212, 108044. [Google Scholar] [CrossRef]
- Zheng, Z.; Li, J.; Qin, L. YOLO-BYTE: An efficient multi-object tracking algorithm for automatic monitoring of dairy cows. Comput. Electron. Agric. 2023, 209, 107857. [Google Scholar] [CrossRef]
- Qiao, Y.; Guo, Y.; He, D. Cattle body detection based on YOLOv5-ASFF for precision livestock farming. Comput. Electron. Agric. 2023, 204, 107579. [Google Scholar] [CrossRef]
- Jin, H.; Meng, G.; Pan, Y.; Zhang, X.; Wang, C. An improved intelligent control system for temperature and humidity in a pig house. Agriculture 2022, 12, 1987. [Google Scholar] [CrossRef]
- Mazzetto, A.M.; Falconer, S.; Ledgard, S. Mapping the carbon footprint of milk production from cattle: A systematic review. J. Dairy Sci. 2022, 105, 9713–9725. [Google Scholar] [CrossRef] [PubMed]
- Wang, X.; Chen, B.; Yang, R.; Liu, K.; Cuan, K.; Cao, M. A Non-Contact and Fast Estimating Method for Respiration Rate of Cows Using Machine Vision. Agriculture 2023, 14, 40. [Google Scholar] [CrossRef]
- Xu, B.; Cui, X.; Ji, W.; Yuan, H.; Wang, J. Apple grading method design and implementation for automatic grader based on improved YOLOv5. Agriculture 2023, 13, 124. [Google Scholar] [CrossRef]
- Ji, W.; Pan, Y.; Xu, B.; Wang, J. A real-time apple targets detection method for picking robot based on ShufflenetV2-YOLOX. Agriculture 2022, 12, 856. [Google Scholar] [CrossRef]
- Hu, T.; Wang, W.; Gu, J.; Xia, Z.; Zhang, J.; Wang, B. Research on Apple Object Detection and Localization Method Based on Improved YOLOX and RGB-D Images. Agronomy 2023, 13, 1816. [Google Scholar] [CrossRef]
- Wang, Z.; Wang, S.; Wang, C.; Zhang, Y.; Zong, Z.; Wang, H.; Su, L.; Du, Y. A non-contact cow estrus monitoring method based on the thermal infrared images of cows. Agriculture 2023, 13, 385. [Google Scholar] [CrossRef]
- Chen, C.; Zhu, W.; Steibel, J.; Siegford, J.; Han, J.; Norton, T. Classification of drinking and drinker-playing in pigs by a video-based deep learning method. Biosyst. Eng. 2020, 196, 1–14. [Google Scholar] [CrossRef]
- He, K.M.; Sun, J.; Tang, X.O. Single image haze removal using dark channel prior. IEEE Trans. Pattern Anal. 2011, 33, 2341–2353. [Google Scholar]
- Jobson, D.J.; Rahman, Z.; Woodell, G.A. Properties and performance of a center/surround Retinex. IEEE Trans. Image Process. 1997, 6, 451–462. [Google Scholar] [CrossRef] [PubMed]
- Wang, S.H.; Zheng, J.; Hu, H.M.; Li, B. Naturalness preserved enhancement algorithm for non-uniform illumination images. IEEE Trans. Image Process. 2013, 22, 3538–3548. [Google Scholar] [CrossRef] [PubMed]
- Li, C.; Guo, J.; Porikli, F.; Pang, Y. LightenNet: A convolutional neural network for weakly illuminated image enhancement. Pattern Recogn. Lett. 2018, 104, 15–22. [Google Scholar] [CrossRef]
- Lv, F.; Lu, F.; Wu, J.; Lim, C. MBLLEN: Low-Light Image/Video Enhancement Using CNNs. BMVC 2018, 220, 4. [Google Scholar]
- Jiang, Y.; Gong, X.; Liu, D.; Cheng, Y.; Fang, C.; Shen, X.; Yang, J.; Zhou, P.; Wang, Z. Enlightengan: Deep light enhancement without paired supervision. IEEE Trans. Image Process. 2021, 30, 2340–2349. [Google Scholar] [CrossRef]
- Guo, C.; Li, C.; Guo, J.; Loy, C.C.; Hou, J.; Kwong, S.; Cong, R. Zero-reference deep curve estimation for low-light image enhancement//Proceedings of the IEEE/CVF conference on computer vision and pattern recognition. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, Seattle, WA, USA, 14–19 June 2020; pp. 1780–1789. [Google Scholar]
- Guo, Y.; Zhang, Z.; He, D.; Niu, J.; Tan, Y. Detection of cow mounting behavior using region geometry and optical flow characteristics. Comput. Electron. Agric. 2019, 163, 104828. [Google Scholar] [CrossRef]
- Howard, A.G.; Zhu, M.; Chen, B.; Kalenichenko, D.; Wang, W.; Weyand, T.; Andreetto, M.; Adam, H. Mobilenets: Efficient convolutional neural networks for mobile vision applications. arXiv 2017, arXiv:1704.04861. [Google Scholar]
- Zhang, X.; Zhou, X.; Lin, M.; Sun, J. Shufflenet: An extremely efficient convolutional neural network for mobile devices. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, Salt Lake City, UT, USA, 18–22 June 2018; pp. 6848–6856. [Google Scholar]
- Buchsbaum, G. A spatial processor model for object colour perception. J. Frankl. Inst. 1980, 310, 1–26. [Google Scholar] [CrossRef]
Models | Unenhanced | Improved Zero-DCE Enhanced | |||||
---|---|---|---|---|---|---|---|
P | R | mAP0.5 | P | R | mAP0.5 | FPS (Frame/s) | |
YOLOv5 | 92.6 | 70.8 | 83.1 | 94.7 | 80.1 | 88.4 | 346.5 |
CenterNet | 94.9 | 67.95 | 75.09 | 92.43 | 71.81 | 79.23 | |
EfficientNet | 87.17 | 74.24 | 83.45 | 91.51 | 78.7 | 85.95 | |
YOLOv7-tiny | 91.6 | 79.2 | 78.7 | 92.9 | 79.8 | 80.9 |
Model | DCE+ Improvement Modules | Detection Results after Image Enhancement | |||||
---|---|---|---|---|---|---|---|
Up-Down Sampling Structure | Self-Attention Gate Mechanism | Kernel Selection Module | ACT Module | P | R | mAP0.5 | |
YOLOv5 | × | × | × | × | 90.8 | 74.2 | 84.7 |
√ | × | × | × | 93.5 | 72.8 | 84.7 | |
√ | √ | × | × | 94.0 | 73.4 | 85.1 | |
√ | √ | √ | × | 93.0 | 75.1 | 85.9 | |
√ | √ | √ | √ | 94.7 | 80.1 | 88.4 |
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Yu, Z.; Guo, Y.; Zhang, L.; Ding, Y.; Zhang, G.; Zhang, D. Improved Lightweight Zero-Reference Deep Curve Estimation Low-Light Enhancement Algorithm for Night-Time Cow Detection. Agriculture 2024, 14, 1003. https://doi.org/10.3390/agriculture14071003
Yu Z, Guo Y, Zhang L, Ding Y, Zhang G, Zhang D. Improved Lightweight Zero-Reference Deep Curve Estimation Low-Light Enhancement Algorithm for Night-Time Cow Detection. Agriculture. 2024; 14(7):1003. https://doi.org/10.3390/agriculture14071003
Chicago/Turabian StyleYu, Zijia, Yangyang Guo, Liyuan Zhang, Yi Ding, Gan Zhang, and Dongyan Zhang. 2024. "Improved Lightweight Zero-Reference Deep Curve Estimation Low-Light Enhancement Algorithm for Night-Time Cow Detection" Agriculture 14, no. 7: 1003. https://doi.org/10.3390/agriculture14071003