Artificial Intelligence Applied to Image Forensics: Advances in the Forensic Field
DOI:
https://doi.org/10.24215/15146774e080Keywords:
digital forensic analysis, forensic examinations, image processing, neural networksAbstract
Forensic analysis plays a crucial role in legal proceedings involving medical and health-related matters. Its significance lies in providing an impartial assessment grounded in scientific medical knowledge. Additionally, forensic evaluations contribute to damage assessment, accountability assignment, and interpretation of medical evidence.
The Forensic Medical Corps of the Judicial Branch of Neuqu´en has compiled a substantial amount of data on judicial assessments conducted, which could be utilized to develop Intelligent Systems that assist professionals in their decision-making processes.
Consequently, there is a need to understand, process, and manipulate both images and the accompanying medical-legal reports. This work presents the results of the development of an Intelligent System for image processing, capable of determining the presence of ecchymosis. To achieve this, a convolutional neural network was configured and trained using a publicly available dataset. Tests were conducted to
evaluate the network’s performance with both black-and-white and color images, considering that the computational volume involved in training for both types of images is a critical factor to be addressed.
Moreover, two approaches for data extraction from forensic reports are presented, which can be either printed or handwritten.
Additionally, a mobile application was developed that allows users to access the trained model and determine, based on an image, whether it corresponds to ecchymosis, indicating the associated reliability percentage of the result.
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