Sharpness-Based Distance Detection
Abstract
:1. Introduction
2. Target Identification and Location
2.1. YOLOv7 Basic Model
2.2. Attention Mechanism
2.3. DeepSORT Algorithm
2.4. Target Detection Experiment
3. Sharpness Assessment
3.1. Image Sharpness Assessment
3.2. Image Sharpness Evaluation at Different Distances
3.3. Definition Ranging for Different Targets
3.4. Result Analysis
4. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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Sharpness Score | Predicted Distance | Actual Distance | Magnitude of Error |
---|---|---|---|
4.73108 | 8.870 m | 8.833 m | ≈0.5% |
4.52128 | 11.391 m | 11.404 m | ≈0.1% |
4.41614 | 13.756 m | 13.802 m | ≈0.3% |
4.37261 | 15.793 m | 15.719 m | ≈0.5% |
4.24381 | 18.692 m | 18.987 m | ≈1.6% |
Experimental Methods | Actual Value | Predicted Value | Magnitude of Error | Actual Value | Predicted Value | Magnitude of Error |
---|---|---|---|---|---|---|
Sharpness ranging method | 8.833 m | 8.870 m | ≈0.5% | 11.404 m | 11.391 m | ≈0.1% |
8.656 m | 8.561 m | ≈1.1% | 11.316 m | 11.291 m | ≈0.2% | |
Distance measuring method combined with YOLO method | 8.833 m | 7.65 m | ≈13% | 11.404 m | 9.49 m | ≈16% |
8.656 m | 7.47 m | ≈14% | 11.316 m | 9.52 m | ≈16% | |
Monocular distance measurement was performed in combination with CNN | 8.833 m | 8.01 m | ≈0.9% | 11.404 m | 10.31 m | ≈1.0% |
8.656 m | 7.89 m | ≈0.8% | 11.316 m | 10.07 m | ≈1.1% |
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Jin, Y.; Zhou, C.; Dai, W. Sharpness-Based Distance Detection. Appl. Sci. 2024, 14, 8913. https://doi.org/10.3390/app14198913
Jin Y, Zhou C, Dai W. Sharpness-Based Distance Detection. Applied Sciences. 2024; 14(19):8913. https://doi.org/10.3390/app14198913
Chicago/Turabian StyleJin, Ying, Cangtao Zhou, and Wanjun Dai. 2024. "Sharpness-Based Distance Detection" Applied Sciences 14, no. 19: 8913. https://doi.org/10.3390/app14198913
APA StyleJin, Y., Zhou, C., & Dai, W. (2024). Sharpness-Based Distance Detection. Applied Sciences, 14(19), 8913. https://doi.org/10.3390/app14198913