Introduction Conventional blood pattern analysis and the reconstruction of the area of origin is a tough, laborious and time-consuming activity. Digital photographs can be used in commercially available software programs to reconstruct the crime scene and perform an automated calculation of the area of origin for blood pattern analysis. However, the current state-of-the-art computer-based techniques to determine the area of origin of bloodstains rely on prospective on-site measurements and simplified ellipse shape fitting of the bloodstains. Methods In the proposed approach, a calibration pattern is used while photographing the crime scene, hence significantly reducing the documentation workload on-site. Additionally, an Active Bloodstain Shape Model (ABSM) is presented as an alternative to ellipse fitting. The ABSM combines a statistical model of possible bloodstain shapes with a regression curve describing the relationship between model shape parameters and impact angle. The model was trained with data acquired from experiments where bloodstains were created under predetermined controlled angles. A Robust Point Matching algorithm was developed to fit the ABSM to a new shape. This algorithm uses outlier detection and an advanced initial alignment of the model to automatically detect and ignore bloodstain tails. The area of origin is calculated by analyzing the intersection points of the linear flight paths with a robust Principal Component Analysis (PCA) that ignores outliers. Conclusions Several experimental validations were carried out to indicate the correct functionality of the approach. The resulting procedure is more accurate and requires less user input than current (commercially) available methods.