Digital Image Identification and Verification Using Maximum and Preliminary Score Approach with Watermarking for Security and Validation Enhancement
Abstract
:1. Introduction
2. Related Work
3. Maximum and Preliminary Score Approach
4. Image Authentication
5. Frame Selection and Average Score Algorithm
- 1.
- Video frame selection based on average using discrete wavelet transform method which firstly identifies the first given input image which may be evaluated as:
- 2.
- Filtering process will be applied using high pass and low pass for decomposition of parents wavelets.
- 3.
- Next level of DWT now applied to first approximation achieved in first step approximation band.
- 4.
- Average of every DWT band is evaluated by dividing image in windows being captured.
- 5.
- If window size is then
- 6.
- Average of every opening now integrated to evaluate the attribute merit of line.
- 7.
- Final total score of images , was obtained by averaging the feature value of each band individually:
- 8.
- For a video image , feature score of frames is denoted by and obtained max-min normalization using
- 9.
- Formerly the outcome of individual structure is evaluated compatible process for structure nomination is carry out to identity best deposit frame [36].
- 10.
- Testing performed for the rich feature frame from the database and verified with the matched score for its perfect authentication.
6. Proposed Model for Identification and Verification
7. Results & Discussions
8. Conclusions
Author Contributions
Funding
Informed Consent Statement
Conflicts of Interest
References
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Image Type | Identification Accuracy Rate (%) | Verification | |
---|---|---|---|
Error (%) | Hit (%) | ||
1. Random | 90.12 | 9.88 | 3.65 |
2. Eigen | 91.54 | 8.64 | 7.45 |
3. Feature trained | 98.33 | 1.67 | 8.43 |
4. Normal feature | 88.89 | 11.11 | 2.34 |
Image Type | Identification Accuracy Rate (%) | Verification | |
---|---|---|---|
Error (%) | Hit (%) | ||
1. Random | 85.62 | 14.38 | 5.63 |
2. Eigen | 91.43 | 8.57 | 7.45 |
3. Feature trained | 93.12 | 6.88 | 9.11 |
4. Normal feature | 90.67 | 9.33 | 3.29 |
Image Type | Identification Accuracy Rate (%) | Verification | |
---|---|---|---|
Error (%) | Hit (%) | ||
1. Random | 85.10 | 14.9 | 1.39 |
2. Eigen | 93.42 | 6.58 | 3.74 |
3. Feature trained | 95.89 | 4.11 | 5.01 |
4. Normal feature | 87.34 | 12.57 | 0.65 |
Image Type | Identification AccuracyRate (%) | Verification | |
---|---|---|---|
Error (%) | Hit (%) | ||
1. Random | 88.39 | 11.61 | 6.87 |
2. Eigen | 98.54 | 1.46 | 2.49 |
3. Feature trained | 99.11 | 0.86 | 9.35 |
4. Normal feature | 90.67 | 9.33 | 4.34 |
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Upadhyay, S.; Kumar, M.; Upadhyay, A.; Verma, S.; Kavita; Hosen, A.S.M.S.; Ra, I.-H.; Kaur, M.; Singh, S. Digital Image Identification and Verification Using Maximum and Preliminary Score Approach with Watermarking for Security and Validation Enhancement. Electronics 2023, 12, 1609. https://doi.org/10.3390/electronics12071609
Upadhyay S, Kumar M, Upadhyay A, Verma S, Kavita, Hosen ASMS, Ra I-H, Kaur M, Singh S. Digital Image Identification and Verification Using Maximum and Preliminary Score Approach with Watermarking for Security and Validation Enhancement. Electronics. 2023; 12(7):1609. https://doi.org/10.3390/electronics12071609
Chicago/Turabian StyleUpadhyay, Shrikant, Mohit Kumar, Aditi Upadhyay, Sahil Verma, Kavita, A. S. M. Sanwar Hosen, In-Ho Ra, Maninder Kaur, and Satnam Singh. 2023. "Digital Image Identification and Verification Using Maximum and Preliminary Score Approach with Watermarking for Security and Validation Enhancement" Electronics 12, no. 7: 1609. https://doi.org/10.3390/electronics12071609
APA StyleUpadhyay, S., Kumar, M., Upadhyay, A., Verma, S., Kavita, Hosen, A. S. M. S., Ra, I. -H., Kaur, M., & Singh, S. (2023). Digital Image Identification and Verification Using Maximum and Preliminary Score Approach with Watermarking for Security and Validation Enhancement. Electronics, 12(7), 1609. https://doi.org/10.3390/electronics12071609