Trends and Challenges in Forensic Image Processing: A Bibliometric Study
DOI:
https://doi.org/10.12928/admj.v6i2.14221Keywords:
Forensic image processing, Forensic artificial intelligence, Criminal investigations;, Forensic mechine learning, Research trendsAbstract
Forensic image processing plays a pivotal role in modern criminal investigations by enhancing, analyzing, and interpreting visual evidence. This bibliometric study aims to evaluate the research trends, influential publications, and collaborative networks in forensic image processing over the past two decades. This study analyzes global research trends in forensic entomology using data from the Scopus database spanning 1962 to 2024, with data visualized through VOSviewer. A total of 4,463 articles were identified, with an average productivity of 72 papers per year. Results reveal a significant increase in research outputs, with dominant contributions from countries excelling in advanced computational technologies. Current hot topics in the field include digital forensic, deep learning, convolutional neural network, and diagnostic imaging. This study provides valuable insights into the evolution of forensic image processing research and identifies future directions for technological advancements and interdisciplinary collaborations.
References
Kapoor N, Sulke P, Pardeshi P, Kakad R, Badiye A. Textbook of Forensic Science. Singapore: Springer Nature Singapore; 2023. doi:10.1007/978-981-99-1377-0
Shipra G, Indu B. Crime scene investigation and forensic evidence: forensic analysis and tools. J Pharm Negat Results. 2023;14:3661-3667. doi:10.47750/pnr.2023.14.02.432
Chavarín Á, Cuevas E, Avalos O, Gálvez J, Pérez-Cisneros M. Contrast enhancement in images by homomorphic filtering and cluster-chaotic optimization. IEEE Access. 2023;11:73803-73822. doi:10.1109/ACCESS.2023.3287559
Mahmood T, Rehman A, Saba T, Nadeem L, Bahaj SAO. Recent advancements and future prospects in active deep learning for medical image segmentation and classification. IEEE Access. 2023;11:113623-113652. doi:10.1109/ACCESS.2023.3313977
Kundu A. Forensic odontology: bridging the gap between dental science and criminal investigation. Int J Ethics Trauma Victimol. 2024:18-27. Available from: https://ijetv.org/index.php/IJETV/article/view/1180. Accessed January 31, 2025.
Sessa F, Esposito M, Cocimano G, Sablone S, Karaboue MAA, Chisari M, et al. Artificial intelligence and forensic genetics: current applications and future perspectives. Appl Sci. 2024;14:2113. doi:10.3390/app14052113
Vodanović M, Subašić M, Milošević DP, Galić I, Brkić H. Artificial intelligence in forensic medicine and forensic dentistry. J Forensic Odontostomatol. 2023;41:30-41.
Khan MS, Afridi U, Ahmed MJ, Zeb B, Ullah I, Hassan MZ. Comprehensive evaluation of artificial intelligence applications in forensic odontology: a systematic review and meta-analysis. IECE Trans Intell Syst. 2024;1:176-189. doi:10.62762/TIS.2024.818917
Kausar S, Khanzada R, Sherazi MA. Comparative study of forensic face recognition and fingerprint during crime scene investigation and the role of artificial intelligence tools in forensics. J Dev Soc Sci. 2024;5. doi:10.47205/jdss.2024(5-I)54
Muthukumaran B, Harshavarthanan L, Dhyaneshwar S, Sharief MZ. Face and iris-based human authentication using deep learning. In: 2023 4th International Conference on Electronics and Sustainable Communication Systems (ICESC). IEEE; 2023:841-846. doi:10.1109/ICESC57686.2023.10193230
Renukadevi P, John S, Shivani N. Forensic science: AI-powered image and audio analysis. In: 2024 5th International Conference on Smart Electronics and Communication (ICOSEC). IEEE; 2024:1519-1525. doi:10.1109/ICOSEC61587.2024.10722068
Zimmermann N, Sieberth T, Dobay A. Automated wound segmentation and classification of seven common injuries in forensic medicine. Forensic Sci Med Pathol. 2023;20:443-451. doi:10.1007/s12024-023-00668-5
Carew RM, Errickson D. Imaging in forensic science: five years on. J Forensic Radiol Imaging. 2019;16:24-33. doi:10.1016/j.jofri.2019.01.002
Wilkinson C, Pizzolato M, De Angelis D, Mazzarelli D, D’Apuzzo A, Liu JC, et al. Post-mortem to ante-mortem facial image comparison for deceased migrant identification. Int J Legal Med. 2024;138:2691-2706. doi:10.1007/s00414-024-03286-0
Queiroz Nogueira Lira R, Geovana Motta de Sousa L, Memoria Pinho ML, Pinto da Silva Andrade de Lima RC, Garcia Freitas P, Scholles Soares Dias B, et al. Deep learning-based human gunshot wounds classification. Int J Legal Med. 2024. doi:10.1007/s00414-024-03355-4
Piraianu AI, Fulga A, Musat CL, Ciobotaru OR, Poalelungi DG, Stamate E, et al. Enhancing the evidence with algorithms: how artificial intelligence is transforming forensic medicine. Diagnostics (Basel). 2023;13:2992. doi:10.3390/diagnostics13182992
Sathyavathi S, Baskaran KR. Human age estimation using deep convolutional neural network based on dental images (orthopantomogram). IETE J Res. 2024;70:1585-1592. doi:10.1080/03772063.2023.2165177
Kumar D, Pandey RC, Mishra AK. A review of image features extraction techniques and their applications in image forensic. Multimed Tools Appl. 2024;83:87801-87902. doi:10.1007/s11042-023-17950-x
S R, U S, Rao SS, Sawkar NP, Devi MS. Image reconstruction and facial feature extraction for criminal identification using machine intelligence (Epic Vision). In: 2024 IEEE International Conference on Contemporary Computing and Communications (InC4). IEEE; 2024:1-6. doi:10.1109/InC460750.2024.10649104
Wahyuni ES, Putri AWK, Pelu NAP, Firdaus, Wiraagni IA. Image processing-based application for determining wound types in forensic medical cases. Jurnal Nasional Teknik Elektro. 2024:12-19. doi:10.25077/jnte.v13n1.1148.2024
Dulla N, Priyadarshini S, Mishra S, Swain SC. Global exploration on bibliometric research articles: a bibliometric analysis. Library Philosophy and Practice. 2021;2021:1-26.
Girish Savadatti S, Srinivasan K, Hu YC. A bibliometric analysis of agent-based systems in cybersecurity and broader security domains: trends and insights. IEEE Access. 2025;13:90-119. doi:10.1109/ACCESS.2024.3520583
Wiraagni IA, Rezadhini M, Setiawan J, Sofyantoro F, Priyono DS, Septriani NI, et al. Research trends on forensic entomology for five decades worldwide. Leg Med (Tokyo). 2024;71:102539. doi:10.1016/j.legalmed.2024.102539
Baas J, Schotten M, Plume A, Côté G, Karimi R. Scopus as a curated, high-quality bibliometric data source for academic research in quantitative science studies. Quant Sci Stud. 2020;1:377-386. doi:10.1162/qss_a_00019
Kirillova OV. Scopus database as a source of representing Bulgarian science to the international academic community: the present and future prospects. Digit Present Preserv Cult Sci Herit. 2017;7:69-78. doi:10.55630/dipp.2017.7.6
van Eck NJ, Waltman L. Software survey: VOSviewer, a computer program for bibliometric mapping. Scientometrics. 2010;84:523-538. doi:10.1007/s11192-009-0146-3
Waltman L, van Eck NJ, Noyons ECM. A unified approach to mapping and clustering of bibliometric networks. J Informetr. 2010;4:629-635. doi:10.1016/j.joi.2010.07.002
Ding Y, Chowdhury GG, Foo S. Bibliometric cartography of information retrieval research by using co-word analysis. Inf Process Manag. 2001;37:817-842. doi:10.1016/S0306-4573(00)00051-0
Mielenz RC. Petrography applied to Portland-cement concrete. In: Reviews in Engineering Geology. Geological Society of America; 1962:1-38. doi:10.1130/REG1-p1
Manaswini D, Ghanta SSV, Manogna TL, Kolakalapudi LNK, Chaitanya GK, Kumar AD. A survey of forensic applications using digital image processing: image improvement case study. In: 2023 7th International Conference on Computing Methodologies and Communication (ICCMC). IEEE; 2023:696-702. doi:10.1109/ICCMC56507.2023.10084079
Russ JC. Forensic Uses of Digital Imaging. 2nd ed. CRC Press; 2016. doi:10.1201/b19159
Dalrymple BE, Smith EJ. Forensic Digital Image Processing: Optimization of Impression Evidence. CRC Press; 2018. doi:10.4324/9781351112239
Amrouni N, Benzaoui A, Bouaouina R, Khaldi Y, Adjabi I, Bouglimina O. Contactless palmprint recognition using binarized statistical image features-based multiresolution analysis. Sensors (Basel). 2022;22:9814. doi:10.3390/s22249814
Lukáš J, Fridrich J, Goljan M. Digital camera identification from sensor pattern noise. IEEE Trans Inf Forensics Secur. 2006;1:205-214. doi:10.1109/TIFS.2006.873602
Popescu AC, Farid H. Exposing digital forgeries by detecting traces of resampling. IEEE Trans Signal Process. 2005;53:758-767. doi:10.1109/TSP.2004.839932
Yang X, Li Y, Lyu S. Exposing deep fakes using inconsistent head poses. 2018.
Chen M, Fridrich J, Goljan M, Lukas J. Determining image origin and integrity using sensor noise. IEEE Trans Inf Forensics Secur. 2008;3:74-90. doi:10.1109/TIFS.2007.916285
Christlein V, Riess C, Jordan J, Riess C, Angelopoulou E. An evaluation of popular copy-move forgery detection approaches. IEEE Trans Inf Forensics Secur. 2012;7:1841-1854. doi:10.1109/TIFS.2012.2218597
Khan MJ, Khan HS, Yousaf A, Khurshid K, Abbas A. Modern trends in hyperspectral image analysis: a review. IEEE Access. 2018;6:14118-14129. doi:10.1109/ACCESS.2018.2812999
Thali MJ, Yen K, Schweitzer W, Vock P, Boesch C, Ozdoba C, et al. Virtopsy, a new imaging horizon in forensic pathology: virtual autopsy by postmortem multislice computed tomography (MSCT) and magnetic resonance imaging (MRI)—a feasibility study. J Forensic Sci. 2003;48:386-403.
Gat N. Imaging spectroscopy using tunable filters: a review. In: Szu HH, Vetterli M, Campbell WJ, Buss JR, eds. Proceedings of SPIE. 2000:50-64. doi:10.1117/12.381686
Popescu AC, Farid H. Exposing digital forgeries in color filter array interpolated images. IEEE Trans Signal Process. 2005;53:3948-3959. doi:10.1109/TSP.2005.855406
Dong J, Wang W, Tan T. CASIA image tampering detection evaluation database. In: 2013 IEEE China Summit and International Conference on Signal and Information Processing. IEEE; 2013:422-426. doi:10.1109/ChinaSIP.2013.6625374
Mahdian B, Saic S. Detection of copy-move forgery using a method based on blur moment invariants. Forensic Sci Int. 2007;171:180-189. doi:10.1016/j.forsciint.2006.11.002
Thali M, Yen K, Schweitzer W, Vock P, Boesch C, Ozdoba C, et al. Virtopsy, a new imaging horizon in forensic pathology: virtual autopsy by postmortem multislice computed tomography (MSCT) and magnetic resonance imaging (MRI)—a feasibility study. J Forensic Sci. 2003;48:1-18. doi:10.1520/jfs2002166
Masi I, Killekar A, Mascarenhas RM, Gurudatt SP, AbdAlmageed W. Two-branch recurrent network for isolating deepfakes in videos. In: Lecture Notes in Computer Science. Vol 12352. Springer; 2020:667-684. doi:10.1007/978-3-030-58571-6_39
Thurzo A, Kosnáčová HS, Kurilová V, Kosmeľ S, Beňuš R, Moravanský N, et al. Use of advanced artificial intelligence in forensic medicine, forensic anthropology and clinical anatomy. Healthcare (Basel). 2021;9:1545. doi:10.3390/healthcare9111545
Jerian M, Paolino S, Cervelli F, Carrato S, Mattei A, Garofano L. A forensic image processing environment for investigation of surveillance video. Forensic Sci Int. 2007;167:207-212. doi:10.1016/j.forsciint.2006.06.048
Zemin C, Xiaoxin L, Jianhuang L, Jun C. Robust optical flow estimation method based on structure-texture aware retinex model and its application on face anti-spoofing. J Image Graph. 2023;28:1445-1461. doi:10.11834/jig.220778
Zheng K, Li B, Zeng J. Document image forgery localization and desensitization localization using the attention mechanism. J Xidian Univ. 2023;50:207-218. doi:10.19665/j.issn1001-2400.20230105
Di Palma A, Bianchi I, Focardi M, Cioffi C, Bonetti S, Dalessandri D. Bitemark analysis comparing the use of digital scans and 3D resin casts. J Forensic Odonto-Stomatol. 2024;42:76-86. doi:10.5281/zenodo.13474602
Cannas ED, Mandelli S, Bestagini P, Tubaro S. Investigating translation invariance and shiftability in CNNs for robust multimedia forensics: a JPEG case study. In: Proceedings of the 2024 ACM Workshop on Information Hiding and Multimedia Security (IH MMSec). ACM; 2024:53-63. doi:10.1145/3658664.3659644
Purnekar N, Abady L, Tondi B, Barni M. Improving the robustness of synthetic images detection by means of print and scan augmentation. In: Proceedings of the 2024 ACM Workshop on Information Hiding and Multimedia Security (IH MMSec). ACM; 2024:65-73. doi:10.1145/3658664.3659635
Epain M, Valette S, Zou K, Faisan S, Heitz F, Croisille P, et al. Sex estimation from coxal bones using deep learning in a population balanced by sex and age. Int J Legal Med. 2024. doi:10.1007/s00414-024-03268-2
Chen J, Liao X, Qian Z, Qin Z. Multi-domain probability estimation network for forgery detection over online social network shared images. In: Proceedings of the IEEE International Conference on Multimedia and Expo (ICME). IEEE; 2024. doi:10.1109/ICME57554.2024.10687645
Weyermann C, Willis S, Margot P, Roux C. Towards more relevance in forensic science research and development. Forensic Sci Int. 2023;348:111592. doi:10.1016/j.forsciint.2023.111592
Gokhale A, Mulay P, Pramod D, Kulkarni R. A bibliometric analysis of digital image forensics. Sci Technol Libr. 2020;39:96-113. doi:10.1080/0194262X.2020.1714529
Koundinya AK, Dixit S, Mahesh G, Sneha S. Characteristic overview of digital image forensics tools. In: Lecture Notes in Networks and Systems. Vol 237. Springer; 2022. doi:10.1007/978-981-16-6407-6_15
Hashmi MF, Keskar AG. Block and fuzzy techniques based forensic tool for detection and classification of image forgery. J Electr Eng Technol. 2015;10:1887-1899. doi:10.5370/JEET.2015.10.4.1887
Shi GF, Huang P, Liu NG, Yu XT, Zhang H, Li SY, et al. Analysis of forensic sciences literature in SCIE from 2008 to 2017. J Forensic Med. 2019;35:30-38. doi:10.12116/j.issn.1004-5619.2019.01.006
Farid H. Image forensics. Annu Rev Vis Sci. 2019;5:549-573. doi:10.1146/annurev-vision-091718-014827
Yu H, Fan B, Xu B, Zhu X. SharpenNet: detecting anti-forensics USM sharpening adversarial examples based on ConvNeXt. J Circuits Syst Comput. 2023. doi:10.1142/S0218126624300034
Beck TS. Image manipulation in scholarly publications: are there ways to an automated solution? J Doc. 2022;78:1184-1198. doi:10.1108/JD-06-2021-0113
Menon V, Prasad B, Kaur M, Kaur H, Pandey D, Dogiwal SR. The Impact of Thrust Technologies on Image Processing. Nova Science Publishers; 2023. doi:10.52305/ATJL4552
Gokhale A, Mulay P, Pramod D, Kulkarni R. A bibliometric analysis of digital image forensics. Sci Technol Libr. 2020;39:96-113. doi:10.1080/0194262X.2020.1714529
Zhang Y. Image engineering in China: 2019. J Image Graph. 2020;25:864-878. doi:10.11834/jig.200102
Shi GF, He XD. Metrological analysis of the projects in the field of forensic science funded by the National Natural Science Foundation of China between 2000 and 2019. Fa Yi Xue Za Zhi. 2020;36:772-773. doi:10.12116/j.issn.1004-5619.2020.06.006
Shueb S, Gul S. Measuring the research funding landscape: a case study of BRICS nations. Glob Knowl Mem Commun. 2025;74:346-369. doi:10.1108/GKMC-08-2022-0192
Xiang D. Analyzing international scientific collaboration in materials science through co-authorship. In: Proceedings of the 19th International Conference on Industrial Engineering and Engineering Management. Springer; 2013:73-83. doi:10.1007/978-3-642-38427-1_9
Randeberg LL, Skallerud B, Langlois NEI, Haugen OA, Svaasand LO. The optics of bruising. In: Welch AJ, van Gemert MJC, eds. Optical-Thermal Response of Laser-Irradiated Tissue. Springer; 2011:825-858. doi:10.1007/978-90-481-8831-4_22
Balhareth AAS, Jamesh M, Zabarah GA, Almotlaq MM, Alabaaltahin MAM, Al Jaarah AHA, et al. The role of forensic medicine in modern criminal justice: a review of current practices and innovations. J Ecohumanism. 2024;3:2699-2707. doi:10.62754/joe.v3i7.4669
Oesterhelweg L. Atmosphere of departure in forensic medicine? Virtopsy basic course. Rechtsmedizin. 2007;17:40-43. doi:10.1007/s00194-006-0425-8
Bruce C, Prassas I, Mokhtar M, Clarke B, Youssef E, Wang C, et al. Transforming diagnostics: the implementation of digital pathology in clinical laboratories. Histopathology. 2024;85:207-214. doi:10.1111/his.15178
Verma A, Chouhan APS, Singh V. Role of artificial intelligence in forensic radiology. Int J Med Toxicol Legal Med. 2023;26:42-48. doi:10.5958/0974-4614.2023.00043.8
Tyagi AK, Kumari S. Artificial intelligence-based cyber security and digital forensics: a review. In: Artificial Intelligence-Enabled Digital Twin for Smart Manufacturing. Wiley; 2025:391-419. doi:10.1002/9781394303601.ch18
Karakuş S, Kaya M, Tuncer SA. Real-time detection and identification of suspects in forensic imagery using advanced YOLOv8 object recognition models. Trait Signal. 2023;40:2029-2039. doi:10.18280/ts.400521
Dunsin D, Ghanem MC, Ouazzane K, Vassilev V. A comprehensive analysis of the role of artificial intelligence and machine learning in modern digital forensics and incident response. Forensic Sci Int Digit Investig. 2024;48:301675. doi:10.1016/j.fsidi.2023.301675
Pappachan P, Adi NS, Firmansyah G, Rahaman M. Deep learning-based forensics and anti-forensics. In: Digital Forensics and Cyber Crime Investigation: Recent Advances and Future Directions. CRC Press; 2024:211-240. doi:10.1201/9781003207573-11
Reedy P. Artificial intelligence in digital forensics. In: Siegel J, Saukko P, Houck M, eds. Encyclopedia of Forensic Sciences. 3rd ed. Vol 1. Elsevier; 2022:170-192. doi:10.1016/B978-0-12-823677-2.00236-1
Path to intellectual revolution in digital forensics. In: AI and Emerging Technologies: Automated Decision-Making, Digital Forensics, and Ethical Considerations. CRC Press; 2024:85-102. doi:10.1201/9781003501152-6
Grispos G, Bastola K. Cyber autopsies: the integration of digital forensics into medical contexts. In: De HAG S, RG A, Santosh KC, Temesgen Z, Kane B, Soda P, eds. Proceedings of the IEEE Symposium on Computer-Based Medical Systems (CBMS). IEEE; 2020:510-513. doi:10.1109/CBMS49503.2020.00102
Bertozzi G, Maglietta F, Salerno M, Caffarelli FP. Forensic radiology: penetrating versus non-penetrating trauma. In: Cattaneo C, Grabherr S, eds. Radiology in Forensic Medicine: From Identification to Post-mortem Imaging. Springer; 2019:157-168. doi:10.1007/978-3-319-96737-0_14
Constanzo B, Di Iorio AH, Greco F, Trigo S. Considerations on digital forensic analysis of medical devices and equipment. In: Pino E, Magjarevic R, De Carvalho P, eds. IFMBE Proceedings. Vol 108. Springer; 2024:235-242. doi:10.1007/978-3-031-59216-4_26
Galante N, Cotroneo R, Furci D, Lodetti G, Casali MB. Applications of artificial intelligence in forensic sciences: current potential benefits, limitations and perspectives. Int J Legal Med. 2023;137:445-458. doi:10.1007/s00414-022-02928-5
Renukadevi P, John S, Shivani N. Forensic science: AI-powered image and audio analysis. In: Proceedings of the 5th International Conference on Smart Electronics and Communication (ICOSEC). IEEE; 2024:1519-1525. doi:10.1109/ICOSEC61587.2024.10722068
Chakraborty S, Mali K. An overview of biomedical image analysis from the deep learning perspective. In: Research Anthology on Improving Medical Imaging Techniques for Analysis and Intervention. IGI Global; 2022:43-59. doi:10.4018/978-1-6684-7544-7.ch003
Bernacki J. Digital camera identification based on analysis of optical defects. Multimed Tools Appl. 2020;79:2945-2963. doi:10.1007/s11042-019-08182-z
Lukáš J, Fridrich J, Goljan M. Digital camera identification from sensor pattern noise. IEEE Trans Inf Forensics Secur. 2006;1:205-214. doi:10.1109/TIFS.2006.873602
Li CT, Satta R. Empirical investigation into the correlation between vignetting effect and the quality of sensor pattern noise. IET Comput Vis. 2012;6:560-566. doi:10.1049/iet-cvi.2012.0044
Wang JL, Li X, Fan JR, Yan JP, Gong ZM, Zhao Y, et al. Integrity of the editing and publishing process is the basis for improving an academic journal’s impact factor. World J Gastroenterol. 2022;28:6168-6202. doi:10.3748/wjg.v28.i43.6168
Campisi P. Editorial. IEEE Trans Inf Forensics Secur. 2018;13:5. doi:10.1109/TIFS.2017.2788318
Campisi P, Kundur D. WIFS 2012 – Proceedings of the 2012 IEEE International Workshop on Information Forensics and Security: Preface. In: WIFS 2012 Proceedings. IEEE; 2012. doi:10.1109/WIFS.2012.6412611
Lukáš J, Fridrich J, Goljan M. Digital “bullet scratches” for images. In: Proceedings of the IEEE International Conference on Image Processing (ICIP). Vol 3. IEEE; 2005:65-68. doi:10.1109/ICIP.2005.1530329
Cattaneo G, Faruolo P, Petrillo UF. Experiments on improving sensor pattern noise extraction for source camera identification. In: Proceedings of the 6th International Conference on Innovative Mobile and Internet Services in Ubiquitous Computing (IMIS). IEEE; 2012:609-616. doi:10.1109/IMIS.2012.35
Honeywell. The future is what we make it. Available from: https://www.honeywell.com/us/en. Accessed January 24, 2025.
Binghamton University. Available from: https://www.binghamton.edu/. Accessed January 24, 2025.
Remya RS, Beevi AB. Novel video camera authentication based on peak to correlation energy of clustered sensor pattern noise. In: Proceedings of the IEEE International Conference on Engineering and Technology (ICETECH). IEEE; 2015. doi:10.1109/ICETECH.2015.7274998
Dafale NN, Naskar R. Sensor pattern noise based source anonymization. In: Proceedings of the 3rd IEEE International Conference on Sensing, Signal Processing and Security (ICSSS). IEEE; 2017:93-98. doi:10.1109/SSPS.2017.8071572
Tubaro S. Research profile. ResearchGate. Available from: https://www.researchgate.net/profile/Stefano-Tubaro. Accessed January 24, 2025.
Liu KJR. Academic and industrial experiences. University of Maryland. Available from: http://www.cspl.umd.edu/kjrliu/academic/. Accessed January 24, 2025.
Jones AW. Bibliometric evaluation of Forensic Science International as a scholarly journal within the subject category legal medicine. Forensic Sci Int Synerg. 2023;7:100438. doi:10.1016/j.fsisyn.2023.100438
Jones AW. The distribution of forensic journals, reflections on authorship practices, peer-review and role of the impact factor. Forensic Sci Int. 2007;165:115-128. doi:10.1016/j.forsciint.2006.05.013
Jesubright JJ, Saravanan P. A scientometric analysis of global forensic science research publications. Library Philosophy and Practice. 2014;2014.
Arthur RM, Humburg PJ, Hoogenboom J, Baiker M, Taylor MC, de Bruin KG. An image-processing methodology for extracting bloodstain pattern features. Forensic Sci Int. 2017;277:122-132. doi:10.1016/j.forsciint.2017.05.022
Wiraagni IA, Trissanto S, Utomo AP, Wahyuni ES, Firdaus, Putri AWK, et al. An application for wound type determination based on image processing in forensic cases. Int J Med Toxicol Forensic Med. 2024;14. doi:10.32598/ijmtfm.v14i02.43899
Goljan M, Fridrich J, Filler T. Large scale test of sensor fingerprint camera identification. In: Proceedings of SPIE. Vol 7254. 2009. doi:10.1117/12.805701
Gloe T, Borowka K, Winkler A. Efficient estimation and large-scale evaluation of lateral chromatic aberration for digital image forensics. In: Proceedings of SPIE. Vol 7541. 2010. doi:10.1117/12.839034
Sharma M, Jha S. Uses of software in digital image analysis: a forensic report. In: Proceedings of SPIE. Vol 7546. 2010. doi:10.1117/12.856292
Kirchner M, Fridrich J. On detection of median filtering in digital images. In: Proceedings of SPIE. Vol 7541. 2010. doi:10.1117/12.839100
Vasilaras A, Papadoudis N, Rizomiliotis P. Artificial intelligence in mobile forensics: a survey of current status, a use case analysis and AI alignment objectives. Forensic Sci Int Digit Investig. 2024;49:301737. doi:10.1016/j.fsidi.2024.301737
Zhang CM. Reform and innovation for development in cross-leap type. Zhongshan Daxue Xuebao/Acta Sci Nat Univ Sunyatseni. 2005;44:124-128.
Zhai W, Zhang N, Hua F. The development of forensic science standards in China. Forensic Sci Int Synerg. 2020;2:187-193. doi:10.1016/j.fsisyn.2020.06.001
Zhai W, Zhang N, Hua F, Han K, Xie Q. China forensic science standards: current situation and problems. Forensic Sci Technol. 2020;45:341-347. doi:10.16467/j.1008-3650.2020.04.003
Schwarck E. Intelligence and informatization: the rise of the ministry of public security in intelligence work in China. China J. 2018;80:1-23. doi:10.1086/697089
Bernot A. Police cloud: functional modularity in China’s cloud public security infrastructure. Regul Gov. 2024. doi:10.1111/rego.12604
Jain AK, Ross AA, Nandakumar K. Introduction to Biometrics. Springer; 2011. doi:10.1007/978-0-387-77326-1
Farid H. Photo Forensics. MIT Press; 2016. doi:10.7551/mitpress/10451.001.0001
Liu Y, Ma J, Song H, Qian Z, Lin X. Chinese universities’ cross-border research collaboration in the social sciences and its impact. Sustainability. 2021;13:10378. doi:10.3390/su131810378
Wagner CS, Bornmann L, Leydesdorff L. Recent developments in China–U.S. cooperation in science. Minerva. 2015;53:199-214. doi:10.1007/s11024-015-9273-6
da Silva RT. Some aspects of “grey literature” in Brazil. Archaeologies. 2010;6:327-336. doi:10.1007/s11759-010-9142-8
Leta J, Pereira JCR, Chaimovich H. The life sciences: the relative contribution of the University of São Paulo to the highest impact factor journals and to those with the largest number of articles, 1980 to 1999. Scientometrics. 2005;63:599-616. doi:10.1007/s11192-005-0230-2
Tiwari A, Kusum S. Role of forensic criminology in access to justice—a critical analysis. Routledge; 2024. doi:10.4324/9781032629346-4
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Copyright (c) 2025 Idha Arfianti WIraagni, Komang Saputra Yadnya , Dewi Widiningsih , Adhitya Bhima Nareshwara , I Putu Eka Ganda Winata , Florantia Setya Nugroho , Refly Dwi Angesti Putri , Syukriadi Hidayat , Elvira Sukma Wahyuni , Firdaus , Didi Erwandi Mohamad Haron
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