Age estimation of bloodstains using smartphones and digital image analysis

Recent studies on bloodstains have focused on determining the time since deposition of bloodstains, which can provide useful temporal information to forensic investigations. This study is the first to use smartphone cameras in combination with a truly low-cost illumination system as a tool to estimate the age of bloodstains. Bloodstains were deposited on various substrates and photographed with a smartphone camera. Three smartphones (Samsung Galaxy S Plus, Apple iPhone 4, and Apple iPad 2) were compared. The environmental effects - temperature, humidity, light exposure, and anticoagulant - on the bloodstain age estimation process were explored. The color values from the digital images were extracted and correlated with time since deposition. Magenta had the highest correlation (R2 = 0.966) and was used in subsequent experiments. The Samsung Galaxy S Plus was the most suitable smartphone as its magenta decreased exponentially with increasing time and had highest repeatability (low variation within and between pictures). The quantifiable color change observed is consistent with well-established hemoglobin denaturation process. Using a statistical classification technique called Random Forests™, we could predict bloodstain age accurately up to 42 days with an error rate of 12%. Additionally, the age of forty blind stains were all correctly predicted, and 83% of mock casework samples were correctly classified. No within- and between-person variations were observed (p > 0.05), while smartphone camera, temperature, humidity, and substrate color influenced the age determination process in different ways. Our technique provides a cheap, rapid, easy-to-use, and truly portable alternative to more complicated analysis using specialized equipment, e.g. spectroscopy and HPLC. No training is necessary with our method, and we envision a smartphone application that could take user inputs of environmental factors and provide an accurate estimate of bloodstain age.