ReviewForensic science international. Synergy2026
Interpol review of forensic image and video analysis, 2022-2025.
Review in Forensic science international. Synergy, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The field of forensic image and video analysis is undergoing a transformation, driven by technological innovation and an increasing demand for scientific proof. This review provides an analysis of the state-of-the-art from 2022 to the present, the progress and challenges across key domains. The amount of digital media has made images and videos central to legal investigations. The same technologies that create this evidence also enable sophisticated manipulation, posing a significant threat to its integrity. Deep learning has emerged as a dominant paradigm, offering powerful new capabilities but also introducing challenges related to transparency and validation. This paper examines the maturation of core forensic practices, including the critical re-evaluation of Photo Response Non-Uniformity (PRNU) for source camera identification in an era of computational photography, and the evolution of image enhancement and authentication techniques. We explore the rapid advancements in content analysis, particularly in deep learning-based methods for detecting digital forgery and steganography, highlighting the ongoing "arms race" between manipulation and detection. In biometric and scene-based analysis, we describe the shift in facial comparison towards a probabilistic likelihood ratio framework for expressing evidential value and review the current state of forensic gait analysis and photogrammetry, including its application in vehicle speed estimation. Throughout this review, we emphasize the central tension between the pace of technological advancement and the crucial, ongoing efforts by international bodies such as ENFSI, SWGDE, FISWG, and Interpol to establish the robust standards, best practices, and validation frameworks necessary for ensuring the admissibility and reliability of digital evidence in court. The paper concludes by key trends and outlining future directions, focusing on the needs for explainability, robustness, and continued international collaboration to bridge the gap between innovation and forensically sound application.
Identifiers
What Socratic holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.