The classification of detected bloodstains into predetermined categories is a crucial component of the so-called bloodstain pattern analysis. As in other forensic disciplines, deep learning methods may help to reduce human subjectivity within this process, may increase the classification accuracy, shorten the calculation time and thus, enable high-throughput analysis. In this work, an approach is presented in which a convolutional neural network (Inception v3) was trained from 965 drip stains (passive origin) and 1595 blood spatters (active origin). The trained CNN was evaluated with a test data set consisting of 366 images of drip stains and blood spatters. The success rate was 99.73% which suggests that neural networks could also be used to automatically classify other classes of bloodstain patterns to speed up the investigation process in the future.

The bloodstains age estimation (BAE) is an essential sub-discipline of forensic science, particularly within the context of bloodstain pattern analysis. Over the past three centuries, multiple methods have been developed for BAE with Ultraviolet-visible (UV-Vis) spectroscopy emerging as one of the most prominent due to the chromatic properties of blood. This article provides a comprehensive review of the detection and elucidation of age-related color changes and the methods for estimating the age of bloodstains based on these changes. It begins with a brief overview of existing BAE methods, then presents the principles of UV-Vis spectroscopy and the chemical changes in hemoglobin that enable accurate BAE with this method. After that key publications from late 18th century studies to recent innovations are reviewed. The review also explores the various external factors influencing the aging process of bloodstains and how these factors have been addressed in forensic research.

Zusammenfassung: Hintergrund: Die forensische Altersschätzung von Blutflecken mittels UV-Vis-Spektroskopie basiert auf der Degradation von Hämoglobinderivaten und bietet eine vielversprechende Methode für die Tatortarbeit. Allerdings erschweren Umweltfaktoren wie Temperatur, Licht und Feuchtigkeit die praktische Anwendung, da sie die Alterungsprozesse beeinflussen. Ziel der Arbeit: Ziel dieser Arbeit ist die Modellierung der Hämoglobinderivatverläufe in alternden Blutflecken. Durch simulationsbasierte Spektren können Blutalterungsprozesse unter verschiedenen Umweltbedingungen mathematisch abgebildet werden, um die forensische Blutanalyse zu verbessern. Methodik: Alternde Vollblutproben wurden unter kontrollierten Bedingungen mittels UV-Vis-Spektroskopie analysiert. Zur Modellierung wurde ein statistisches Modell mit der Hamiltonian-Monte-Carlo(HMC)-Methode entwickelt. Der iterative Prozess umfasste die Identifikation spektraler Einflüsse, deren Integration ins Modell und eine schrittweise Optimierung der Parameter. Ergebnisse und Diskussion: Die Modelle ermöglichen eine realitätsnahe Simulation der Hämoglobinderivatverläufe, die mit experimentellen Daten gut übereinstimmen. Die Ergebnisse zeigen das Potenzial statistischer Modellierung zur Ergänzung experimenteller Untersuchungen und Verbesserung der forensischen UV-Vis-Spektroskopie. Weitere Arbeiten sind nötig, um Umwelteinflüsse detaillierter zu erfassen. Graphic

In the realm of forensic science, the analysis and visualization of data and traces rely heavily on the interpretation of colors. This chapter delves into the multifaceted role colors play in forensic investigations, exploring their significance in various domains, such as bloodstain analysis, fingerprint examination, image forensics, and the study of artificial light sources. From discerning the age of bloodstains to identifying manipulated digital images, color analysis emerges as a pivotal tool in unraveling crime events and establishing facts crucial for legal proceedings. Through a discussion of selected forensic methods, this chapter highlights the diverse applications of color analysis and emphasizes the need for standardized approaches to ensure the accuracy and reliability of forensic investigations. Looking ahead, the continuous advancement of technologies and methodologies in color analysis promises to enhance further the efficacy of forensic science in solving crimes.