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RENK TUTARSIZLIĞI PROBLEMLERİ VE ÇÖZÜMLERİ: BİR ARAŞTIRMA

Year 2023, Volume: 11 Issue: 3, 1635 - 1654, 31.07.2023
https://doi.org/10.29130/dubited.1125321

Abstract

Renk tutarsızlığı problemi görüntü sahteciliği, görüntü iç boyama, kare jigsaw puzzle, görüntü birleştirme gibi birçok farklı alanı yakından ilgilendiren güncel bir disiplinlerarası problemdir. Ancak literatürde renk tutarsızlığı problemini genel bir çerçevede ele alıp inceleyen herhangi bir araştırma çalışması bulunmamaktadır. Bu çalışma ile renk tutarsızlığı problemi ele alınarak genel bir sınıflandırma yöntemi ilk defa önerilmiştir. Bu çalışma sonucunda renk tabanlı yöntemler kullanılarak ilgili problemlerin çözülebileceği ve bu problemlerin çözümünde ağırlıklı olarak RGB, CIE Lab ve YCbCr renk uzaylarının tercih edildiği belirlenmiştir. İncelenen çalışmalarda görüntü iç boyama probleminde derin öğrenme algoritmalarının daha fazla kullanıldığı belirlenmiştir. Çalışmalarda PSNR, SSIM gibi değerlendirme metriklerinin kullanıldığı görülmüştür. Sonuç olarak bu çalışma ile renk tutarsızlığı ile uğraşacak araştırmacılara önemli bir yol haritası sunulmuştur.

References

  • [1] https://www.britannica.com/dictionary/consistency Erişim Tarihi: 15.05.2022
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  • [4] Y. Wu, W. AbdAlmageed, and P. Natarajan, “ManTra-Net: Manipulation Tracing Network for Detection and Localization of Image Forgeries With Anomalous Features.” 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2019.
  • [5] T. Wang, H. Ouyang, and Q. Chen, “Image Inpainting with External-internal Learning and Monochromic Bottleneck.” 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
  • [6] J. Jam, C. Kendrick, K. Walker, V. Drouard, J. G.-S. Hsu, and M. H. Yap, “A comprehensive review of past and present image inpainting methods.” Computer Vision and Image Understanding, vol. 203, p. 103147, 2021.
  • [7] https://www.scopus.com/ Erişim Tarihi: 15.05.2022
  • [8] N. B. Warif, A. W. Wahab, M. Y. Idris, R. Ramli, R. Salleh, S. Shamshirband, and K.-K. R. Choo, “Copy-move forgery detection: Survey, challenges and Future Directions,” Journal of Network and Computer Applications, vol. 75, pp. 259–278, 2016.
  • [9] C. N. Bharti and P. Tandel, “A survey of image forgery detection techniques.” 2016 International Conference on Wireless Communications, Signal Processing and Networking (WiSPNET), 2016.
  • [10] K. Liu, W. Lu, C. Lin, X. Huang, X. Liu, Y. Yeung, and Y. Xue, “Copy move forgery detection based on keypoint and Patch Match,” Multimedia Tools and Applications, vol. 78, no. 22, pp. 31387–31413, 2019.
  • [11] A. Araz Rajab, R. Mohd Shafry Mohd, and G. B. Sulong, “Literature Review: Detection of Image Splicing Forgery,” International Journal of Applied Engineering Research, vol. 12, pp 11855-11861, 2017.
  • [12] M. Isaac and M. Wilscy, "Image forgery detection using region–based Rotation invariant Co-occurrences among adjacent LBPs", Journal of Intelligent Fuzzy Systems, vol. 34, no. 3, pp. 1679-1690, 2018.
  • [13] J. Jam, C. Kendrick, K. Walker, V. Drouard, J. Hsu and M. Yap, "A comprehensive review of past and present image inpainting methods", Computer Vision and Image Understanding, vol. 203, p. 103147, 2021.
  • [14] S. Zarif, I. Faye, and D. Rohaya, “Image Completion: Survey and Comparative Study,” International Journal of Pattern Recognition and Artificial Intelligence, vol. 29, no. 03, p. 1554001, Apr. 2015.
  • [15] F. Kleber, R. Sablatnig, “A survey of techniques for document and archaeology artefact reconstruction.” 10th International Conference on Document Analysis and Recognition. IEEE, p. 1061-1065, 2009.
  • [16] D. Sholomon, O. E. David, and N. S. Netanyahu, “An automatic solver for very large jigsaw puzzles using genetic algorithms,” Genetic Programming and Evolvable Machines, vol. 17, no. 3, pp. 291–313, Feb. 2016.
  • [17] R. Xie, M. Xia, J. Yao, and L. Li, “Guided color consistency optimization for image mosaicking,” ISPRS Journal of Photogrammetry and Remote Sensing, vol. 135, pp. 43–59, Jan. 2018.
  • [18] M. Xia, J. Yao, R. Xie, M. Zhang, and J. Xiao, “Color Consistency Correction Based on Remapping Optimization for Image Stitching.” 2017 IEEE International Conference on Computer Vision Workshops (ICCVW), 2017.
  • [19] P. Ganesan, B. S. Sathish, K. Vasanth, V. G. Sivakumar, M. Vadivel, and C. N. Ravi, “A Comprehensive Review of the Impact of Color Space on Image Segmentation.” 2019 5th International Conference on Advanced Computing & Communication Systems (ICACCS), 2019.
  • [20] A. Sahay and A. Gautam, “Comparison between SIFT and SURF image forgery Algorithms,” International Journal of Computer Applications, vol. 164, no. 2, pp. 9–11, Apr. 2017.
  • [21] D. Mondal, Y. Wang, and S. Durocher, “Robust Solvers for Square Jigsaw Puzzles.” 2013 International Conference on Computer and Robot Vision, 2013.
  • [22] H. Niu, Q. Lu, and C. Wang, “Color Correction Based on Histogram Matching and Polynomial Regression for Image Stitching.” 2018 IEEE 3rd International Conference on Image, Vision and Computing (ICIVC), 2018.
  • [23] A. Hore and D. Ziou, “Image Quality Metrics: PSNR vs. SSIM.” 2010 20th International Conference on Pattern Recognition, 2010.
  • [24] S. Dhivya, J. Sangeetha, and B. Sudhakar, “Copy-move forgery detection using SURF feature extraction and SVM supervised learning technique.” Soft Computing, vol. 24, no. 19, pp. 14429-14440, 2020.
  • [25] A. V. Malviya and S. A. Ladhake, “Pixel Based Image Forensic Technique for Copy-move Forgery Detection Using Auto Color Correlogram.” Procedia Computer Science, vol. 79, pp. 383-390, 2016.
  • [26] A. Abrahim, M. Rahim and G. Sulong, "Splicing image forgery identification based on artificial neural network approach and texture features", Cluster Computing, vol. 22, no. 1, pp. 647-660, 2018.
  • [27] Z. Fang, S. Wang, and X. Zhang, “Image Splicing Detection Using Color Edge Inconsistency.” 2010 International Conference on Multimedia Information Networking and Security, 2010.
  • [28] M. Habibi, H. Hassanpour, “Splicing Image Forgery Detection and Localization Based on Color Edge Inconsistency using Statistical Dispersion Measures.” International Journal of Engineering, vol. 34, no. 1, 2021.
  • [29] S. Zhe and S. Peng, “Authentication of splicing manipulation by exposing inconsistency in color shift.” Multimedia Tools and Applications, vol. 79, no. 11, pp. 8235-8248, 2020.
  • [30] J. Stanton, K. Hirakawa, S. McCloskey, “Detecting Image Forgery Based On Color Phenomenology”. In CVPR Workshops (pp. 138-145), 2019.
  • [31] V. Tuba, R. Jovanovic, and M. Tuba, “Digital image forgery detection based on shadow HSV inconsistency.” 2017 5th International Symposium on Digital Forensic and Security (ISDFS), 2017.
  • [32] Y. Zhou, C. Barnes, E. Shechtman, and S. Amirghodsi, “TransFill: Reference-guided image inpainting by merging multiple color and spatial transformations,” 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
  • [33] P. Zhou, N. Yu, Z. Wu, L. Davis, A. Shrivastava, “Deep video inpainting detection” arXiv preprint arXiv:2101.11080, 2021.
  • [34] M. Akbari, M. Mohrekesh, K. Najariani, N. Karimi, S. Samavi, and S. Soroushmehr, “Adaptive Specular Reflection Detection and Inpainting in Colonoscopy Video Frames.” 2018 25th IEEE International Conference on Image Processing (ICIP), 2018.
  • [35] V. K. Alilou and F. Yaghmaee, “Application of GRNN neural network in non-texture image inpainting and restoration.” Pattern Recognition Letters, vol. 62, pp. 24-31, 2015,
  • [36] I.-M. Ciortan, S. George, and J. Y. Hardeberg, “Colour-Balanced Edge-Guided Digital Inpainting: Applications on Artworks.” Sensors, vol. 21, no. 6, p. 2091, 2021.
  • [37] D. Cao, L. Chen, and Y. Liu, “Solving jigsaw puzzle with symbol matrixes.” 2016 IEEE/ACIS 15th International Conference on Computer and Information Science (ICIS), 2016.
  • [38] G. Paikin and A. Tal, “Solving multiple square jigsaw puzzles with missing pieces.” 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2015.
  • [39] H.-C. Shih, J.-L. Lu, and C.-H. Ma, “Square Puzzle Solving Using Border Compatibility Matching.” 2019 16th IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS), 2019.
  • [40] N. Guerroui and H. Séridi, “Solving computational square jigsaw puzzles with a novel pairwise compatibility measure.” Journal of King Saud University - Computer and Information Sciences, vol. 32, no. 8, pp. 928-939, 2020.
  • [41] D. Kim, D. Cho, D. Yoo, and I. S. Kweon, “Learning Image Representations by Completing Damaged Jigsaw Puzzles.” 2018 IEEE Winter Conference on Applications of Computer Vision (WACV), 2018.
  • [42] Q.-C. Tian and L. Cohen, “Histogram-Based Color Transfer for Image Stitching.” Journal of Imaging, vol. 3, no. 3, p. 38, 2017.
  • [43] C. Wang, Z. Gao, and Q. Lu, “Parallax-Based Color Correction in Image Stitching.” 2020 IEEE 5th International Conference on Image, Vision and Computing (ICIVC), 2020.
Year 2023, Volume: 11 Issue: 3, 1635 - 1654, 31.07.2023
https://doi.org/10.29130/dubited.1125321

Abstract

References

  • [1] https://www.britannica.com/dictionary/consistency Erişim Tarihi: 15.05.2022
  • [2] A. H. Saber, M. A. Khan, and B. G. Mejbel, “A Survey on Image Forgery Detection Using Different Forensic Approaches.” Advances in Science, Technology and Engineering Systems Journal, vol. 5, no. 3, pp. 361-370, 2020.
  • [3] S. Mushtaq and A. H. Mir, “Image Copy Move Forgery Detection: A Review.” International Journal of Future Generation Communication and Networking, vol. 11, no. 2, pp. 11-22, 2018, doi: 10.14257/ijfgcn.2018.11.2.02.
  • [4] Y. Wu, W. AbdAlmageed, and P. Natarajan, “ManTra-Net: Manipulation Tracing Network for Detection and Localization of Image Forgeries With Anomalous Features.” 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2019.
  • [5] T. Wang, H. Ouyang, and Q. Chen, “Image Inpainting with External-internal Learning and Monochromic Bottleneck.” 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
  • [6] J. Jam, C. Kendrick, K. Walker, V. Drouard, J. G.-S. Hsu, and M. H. Yap, “A comprehensive review of past and present image inpainting methods.” Computer Vision and Image Understanding, vol. 203, p. 103147, 2021.
  • [7] https://www.scopus.com/ Erişim Tarihi: 15.05.2022
  • [8] N. B. Warif, A. W. Wahab, M. Y. Idris, R. Ramli, R. Salleh, S. Shamshirband, and K.-K. R. Choo, “Copy-move forgery detection: Survey, challenges and Future Directions,” Journal of Network and Computer Applications, vol. 75, pp. 259–278, 2016.
  • [9] C. N. Bharti and P. Tandel, “A survey of image forgery detection techniques.” 2016 International Conference on Wireless Communications, Signal Processing and Networking (WiSPNET), 2016.
  • [10] K. Liu, W. Lu, C. Lin, X. Huang, X. Liu, Y. Yeung, and Y. Xue, “Copy move forgery detection based on keypoint and Patch Match,” Multimedia Tools and Applications, vol. 78, no. 22, pp. 31387–31413, 2019.
  • [11] A. Araz Rajab, R. Mohd Shafry Mohd, and G. B. Sulong, “Literature Review: Detection of Image Splicing Forgery,” International Journal of Applied Engineering Research, vol. 12, pp 11855-11861, 2017.
  • [12] M. Isaac and M. Wilscy, "Image forgery detection using region–based Rotation invariant Co-occurrences among adjacent LBPs", Journal of Intelligent Fuzzy Systems, vol. 34, no. 3, pp. 1679-1690, 2018.
  • [13] J. Jam, C. Kendrick, K. Walker, V. Drouard, J. Hsu and M. Yap, "A comprehensive review of past and present image inpainting methods", Computer Vision and Image Understanding, vol. 203, p. 103147, 2021.
  • [14] S. Zarif, I. Faye, and D. Rohaya, “Image Completion: Survey and Comparative Study,” International Journal of Pattern Recognition and Artificial Intelligence, vol. 29, no. 03, p. 1554001, Apr. 2015.
  • [15] F. Kleber, R. Sablatnig, “A survey of techniques for document and archaeology artefact reconstruction.” 10th International Conference on Document Analysis and Recognition. IEEE, p. 1061-1065, 2009.
  • [16] D. Sholomon, O. E. David, and N. S. Netanyahu, “An automatic solver for very large jigsaw puzzles using genetic algorithms,” Genetic Programming and Evolvable Machines, vol. 17, no. 3, pp. 291–313, Feb. 2016.
  • [17] R. Xie, M. Xia, J. Yao, and L. Li, “Guided color consistency optimization for image mosaicking,” ISPRS Journal of Photogrammetry and Remote Sensing, vol. 135, pp. 43–59, Jan. 2018.
  • [18] M. Xia, J. Yao, R. Xie, M. Zhang, and J. Xiao, “Color Consistency Correction Based on Remapping Optimization for Image Stitching.” 2017 IEEE International Conference on Computer Vision Workshops (ICCVW), 2017.
  • [19] P. Ganesan, B. S. Sathish, K. Vasanth, V. G. Sivakumar, M. Vadivel, and C. N. Ravi, “A Comprehensive Review of the Impact of Color Space on Image Segmentation.” 2019 5th International Conference on Advanced Computing & Communication Systems (ICACCS), 2019.
  • [20] A. Sahay and A. Gautam, “Comparison between SIFT and SURF image forgery Algorithms,” International Journal of Computer Applications, vol. 164, no. 2, pp. 9–11, Apr. 2017.
  • [21] D. Mondal, Y. Wang, and S. Durocher, “Robust Solvers for Square Jigsaw Puzzles.” 2013 International Conference on Computer and Robot Vision, 2013.
  • [22] H. Niu, Q. Lu, and C. Wang, “Color Correction Based on Histogram Matching and Polynomial Regression for Image Stitching.” 2018 IEEE 3rd International Conference on Image, Vision and Computing (ICIVC), 2018.
  • [23] A. Hore and D. Ziou, “Image Quality Metrics: PSNR vs. SSIM.” 2010 20th International Conference on Pattern Recognition, 2010.
  • [24] S. Dhivya, J. Sangeetha, and B. Sudhakar, “Copy-move forgery detection using SURF feature extraction and SVM supervised learning technique.” Soft Computing, vol. 24, no. 19, pp. 14429-14440, 2020.
  • [25] A. V. Malviya and S. A. Ladhake, “Pixel Based Image Forensic Technique for Copy-move Forgery Detection Using Auto Color Correlogram.” Procedia Computer Science, vol. 79, pp. 383-390, 2016.
  • [26] A. Abrahim, M. Rahim and G. Sulong, "Splicing image forgery identification based on artificial neural network approach and texture features", Cluster Computing, vol. 22, no. 1, pp. 647-660, 2018.
  • [27] Z. Fang, S. Wang, and X. Zhang, “Image Splicing Detection Using Color Edge Inconsistency.” 2010 International Conference on Multimedia Information Networking and Security, 2010.
  • [28] M. Habibi, H. Hassanpour, “Splicing Image Forgery Detection and Localization Based on Color Edge Inconsistency using Statistical Dispersion Measures.” International Journal of Engineering, vol. 34, no. 1, 2021.
  • [29] S. Zhe and S. Peng, “Authentication of splicing manipulation by exposing inconsistency in color shift.” Multimedia Tools and Applications, vol. 79, no. 11, pp. 8235-8248, 2020.
  • [30] J. Stanton, K. Hirakawa, S. McCloskey, “Detecting Image Forgery Based On Color Phenomenology”. In CVPR Workshops (pp. 138-145), 2019.
  • [31] V. Tuba, R. Jovanovic, and M. Tuba, “Digital image forgery detection based on shadow HSV inconsistency.” 2017 5th International Symposium on Digital Forensic and Security (ISDFS), 2017.
  • [32] Y. Zhou, C. Barnes, E. Shechtman, and S. Amirghodsi, “TransFill: Reference-guided image inpainting by merging multiple color and spatial transformations,” 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
  • [33] P. Zhou, N. Yu, Z. Wu, L. Davis, A. Shrivastava, “Deep video inpainting detection” arXiv preprint arXiv:2101.11080, 2021.
  • [34] M. Akbari, M. Mohrekesh, K. Najariani, N. Karimi, S. Samavi, and S. Soroushmehr, “Adaptive Specular Reflection Detection and Inpainting in Colonoscopy Video Frames.” 2018 25th IEEE International Conference on Image Processing (ICIP), 2018.
  • [35] V. K. Alilou and F. Yaghmaee, “Application of GRNN neural network in non-texture image inpainting and restoration.” Pattern Recognition Letters, vol. 62, pp. 24-31, 2015,
  • [36] I.-M. Ciortan, S. George, and J. Y. Hardeberg, “Colour-Balanced Edge-Guided Digital Inpainting: Applications on Artworks.” Sensors, vol. 21, no. 6, p. 2091, 2021.
  • [37] D. Cao, L. Chen, and Y. Liu, “Solving jigsaw puzzle with symbol matrixes.” 2016 IEEE/ACIS 15th International Conference on Computer and Information Science (ICIS), 2016.
  • [38] G. Paikin and A. Tal, “Solving multiple square jigsaw puzzles with missing pieces.” 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2015.
  • [39] H.-C. Shih, J.-L. Lu, and C.-H. Ma, “Square Puzzle Solving Using Border Compatibility Matching.” 2019 16th IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS), 2019.
  • [40] N. Guerroui and H. Séridi, “Solving computational square jigsaw puzzles with a novel pairwise compatibility measure.” Journal of King Saud University - Computer and Information Sciences, vol. 32, no. 8, pp. 928-939, 2020.
  • [41] D. Kim, D. Cho, D. Yoo, and I. S. Kweon, “Learning Image Representations by Completing Damaged Jigsaw Puzzles.” 2018 IEEE Winter Conference on Applications of Computer Vision (WACV), 2018.
  • [42] Q.-C. Tian and L. Cohen, “Histogram-Based Color Transfer for Image Stitching.” Journal of Imaging, vol. 3, no. 3, p. 38, 2017.
  • [43] C. Wang, Z. Gao, and Q. Lu, “Parallax-Based Color Correction in Image Stitching.” 2020 IEEE 5th International Conference on Image, Vision and Computing (ICIVC), 2020.
There are 43 citations in total.

Details

Primary Language Turkish
Subjects Engineering
Journal Section Articles
Authors

Melike Bektaş 0000-0002-1944-1928

Seçkin Yılmaz 0000-0001-6791-1536

Turgay Tugay Bilgin 0000-0002-9245-5728

Publication Date July 31, 2023
Published in Issue Year 2023 Volume: 11 Issue: 3

Cite

APA Bektaş, M., Yılmaz, S., & Bilgin, T. T. (2023). RENK TUTARSIZLIĞI PROBLEMLERİ VE ÇÖZÜMLERİ: BİR ARAŞTIRMA. Düzce Üniversitesi Bilim Ve Teknoloji Dergisi, 11(3), 1635-1654. https://doi.org/10.29130/dubited.1125321
AMA Bektaş M, Yılmaz S, Bilgin TT. RENK TUTARSIZLIĞI PROBLEMLERİ VE ÇÖZÜMLERİ: BİR ARAŞTIRMA. DUBİTED. July 2023;11(3):1635-1654. doi:10.29130/dubited.1125321
Chicago Bektaş, Melike, Seçkin Yılmaz, and Turgay Tugay Bilgin. “RENK TUTARSIZLIĞI PROBLEMLERİ VE ÇÖZÜMLERİ: BİR ARAŞTIRMA”. Düzce Üniversitesi Bilim Ve Teknoloji Dergisi 11, no. 3 (July 2023): 1635-54. https://doi.org/10.29130/dubited.1125321.
EndNote Bektaş M, Yılmaz S, Bilgin TT (July 1, 2023) RENK TUTARSIZLIĞI PROBLEMLERİ VE ÇÖZÜMLERİ: BİR ARAŞTIRMA. Düzce Üniversitesi Bilim ve Teknoloji Dergisi 11 3 1635–1654.
IEEE M. Bektaş, S. Yılmaz, and T. T. Bilgin, “RENK TUTARSIZLIĞI PROBLEMLERİ VE ÇÖZÜMLERİ: BİR ARAŞTIRMA”, DUBİTED, vol. 11, no. 3, pp. 1635–1654, 2023, doi: 10.29130/dubited.1125321.
ISNAD Bektaş, Melike et al. “RENK TUTARSIZLIĞI PROBLEMLERİ VE ÇÖZÜMLERİ: BİR ARAŞTIRMA”. Düzce Üniversitesi Bilim ve Teknoloji Dergisi 11/3 (July 2023), 1635-1654. https://doi.org/10.29130/dubited.1125321.
JAMA Bektaş M, Yılmaz S, Bilgin TT. RENK TUTARSIZLIĞI PROBLEMLERİ VE ÇÖZÜMLERİ: BİR ARAŞTIRMA. DUBİTED. 2023;11:1635–1654.
MLA Bektaş, Melike et al. “RENK TUTARSIZLIĞI PROBLEMLERİ VE ÇÖZÜMLERİ: BİR ARAŞTIRMA”. Düzce Üniversitesi Bilim Ve Teknoloji Dergisi, vol. 11, no. 3, 2023, pp. 1635-54, doi:10.29130/dubited.1125321.
Vancouver Bektaş M, Yılmaz S, Bilgin TT. RENK TUTARSIZLIĞI PROBLEMLERİ VE ÇÖZÜMLERİ: BİR ARAŞTIRMA. DUBİTED. 2023;11(3):1635-54.