Can Hu, Hongcheng Mei, Hongling Guo, Ping Wang, Yajun Li, Haiyan Li, Jun Zhu
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引用次数: 2
Abstract
Color is an important characteristic of textile, and its analysis is of great significance for the forensic characterization of textile. The colorimetry method based on visual observation provides a subjective assessment; the instrument-based color analysis method is objective but requires expensive equipment and professional technicians. In this study, a smartphone-based machine vision method for color analysis was established. A smartphone with a camera was used for image acquisition, and the free software ImageJ was used for image processing. The captured RGB image was first converted to a Lab Stack, and then the target area was selected for L*a*b* value analysis. The influence of acquisition equipment, light source, illumination/photography angle and distance, and sample on color analysis was investigated. Fifteen red textile pieces were analyzed using optimized machine vision methods, and the results were compared with those obtained using the microspectrophotometry by both hierarchical cluster analysis and K-means clustering method. The results of the two methods were consistent, thereby confirming the reliability of the machine vision method. The smartphone-based machine vision color analysis method is cheap, simple, accurate, and objective; thus, it has great potential to be widely used in forensic science.
期刊介绍：
Forensic Chemistry publishes high quality manuscripts focusing on the theory, research and application of any chemical science to forensic analysis. The scope of the journal includes fundamental advancements that result in a better understanding of the evidentiary significance derived from the physical and chemical analysis of materials. The scope of Forensic Chemistry will also include the application and or development of any molecular and atomic spectrochemical technique, electrochemical techniques, sensors, surface characterization techniques, mass spectrometry, nuclear magnetic resonance, chemometrics and statistics, and separation sciences (e.g. chromatography) that provide insight into the forensic analysis of materials. Evidential topics of interest to the journal include, but are not limited to, fingerprint analysis, drug analysis, ignitable liquid residue analysis, explosives detection and analysis, the characterization and comparison of trace evidence (glass, fibers, paints and polymers, tapes, soils and other materials), ink and paper analysis, gunshot residue analysis, synthetic pathways for drugs, toxicology and the analysis and chemistry associated with the components of fingermarks. The journal is particularly interested in receiving manuscripts that report advances in the forensic interpretation of chemical evidence. Technology Readiness Level: When submitting an article to Forensic Chemistry, all authors will be asked to self-assign a Technology Readiness Level (TRL) to their article. The purpose of the TRL system is to help readers understand the level of maturity of an idea or method, to help track the evolution of readiness of a given technique or method, and to help filter published articles by the expected ease of implementation in an operation setting within a crime lab.
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