Nabanita Basu

Crime scene reconstruction—Sex prediction from blood stained foot sole impressions

It is often difficult to predict the sex of an individual based on bloody incomplete footprints. However, such prints/impressions are particularly common in a crime scene. Again variability in the texture, color of the target surface has an impact on the bloodstained impression formed. The study of bare foot, footprint, footwear (i.e. shoe, canvas etc.) within the legal context is referred to as forensic podiatry. Based on the fact that it is possible to predict the sex of an individual from footprint impressions, an automated model has been proposed in this paper for analyzing the sex of an individual from his/her broken/incomplete footprint impressions based on morphological features alone. Five male and female volunteers aged between 20 to 65 years participated in dataset development. Keeping the blood volume constant and having stepped on differently shaped porcine blood pools, the individuals were asked to walk on herbarium sheets. The footprints were recorded and documented in accordance with the guidelines in place for physical evidence documentation within the forensic domain. The morphological features that were extracted from each of the footprint impressions are footprint length, footprint breadth, angle of walking, approximated heel radius etc. Using exhaustive cross validation technique, the dataset was divided into training and test set. Non-redundant, relevant features that are particularly effective at sex prediction were marked out using the relief algorithm in coherence with the correlation metric. Supervised learning techniques were used on the dataset to predict the sex of the owner of an unknown footprint. The study concentrates on morphological features in order to deal with bloodstain footprint transfer stains formed on any non-porous/non-absorbent surfaces such as cemented floor, glass, mosaic floor space, colored and designed tiled floor spaces. Features such as the angle of walking and foot breadth were found to be particularly influential in sex prediction from incomplete bloodstained foot sole impressions. In comparison to a system for sex prediction from complete footprint impressions (82.2%), the automated system developed on incomplete foot impressions recorded an accuracy level of 83.47%.

2D Source area prediction based on physical characteristics of a regular, passive blood drip stain

Violent criminal acts are often accompanied by dynamic blood shedding events. Bloodstain pattern analysis particularly deals with estimation of the dynamic blood shedding events from the static bloodstain patterns that have been left at the scene. Of all the stain patterns present at a crime scene, drip stain patterns are common stain patterns one would expect to document at a violent crime scene. The paper documents statistically significant correlations between different physical parameters, such as fall height, total number of spines associated with each stain. Statistical significant correlation between the angle of impact and the total number of spines associated with each stain pattern has been established in this work. The paper propounds that the breadth of a regular drip stain is particularly significant in making predictions empirically as also statistically about the surface area from which blood has dripped leading to the formation of a particular drip stain. A data model has been developed using machine learning techniques to predict the range of surface radius from which blood has dripped and lead to the formation of a particular drip stain (Accuracy: 97.53%, Sensitivity=0.9481, Specificity=1).

An Evidence Based Study of the Different Factors that Influence the Formation of Hammer Transfer Stains in a Crime Scene

Weapon transfer stains in a crime scene are often difficult to interpret. Given the large number of hammer hit events that take place each year, this work is largely aimed at analyzing the different factors that influence and distort regular hammer transfer stains. Different physical mechanisms under identical conditions influence the formation of distinct transfer stain patterns. This is the basic highlight of this study. By experimentation, the authors are of the view that the quantity of blood attached to the surface area of a hammer, the surface area of the hammer exposed to blood, the dimensions of the hammer, the angle of inclination at the time of fall, hardness of the target surface, friction coefficient of the hammer material, texture of the target surface influence the transfer stain formed. Again the velocity of hit, the undulations in the hammer, the depth of blood pool, hammer weight all have significant effect on the transfer stain pattern formed. The significance of the height of fall and the edge that touches the target surface first, cannot be particularly ruled out in analyzing hammer transfer stain patterns. The relevance of the article lies in the fact that analysts having clear idea of how these different factors could affect the formation of different weapon transfer stain patterns, shall be in a better position at understanding the probable mechanism that might have led to the formation of the stain. This knowledge is transferable to the study of other murder weapon transfer stain interpretation and shall aid proper sequencing of segments in a criminal event.

Initial data release of regular blood drip stain created by varying fall height, angle of impact and source dimension

The dataset developed consists of 108 blood drip stains developed with fresh porcine blood, blood admixed with different dosage of Warfarin and Heparin, respectively. For each particular blood type (i.e. fresh blood, blood admixed with Warfarin at different dosage and blood admixed with Heparin at varied dosage) stain patterns were created by passive dripping of blood from a 2.5 cm3 subcutaneous syringe with needle filled to capacity, at 30°, 60° and 90° angle of impact with corresponding fall height of 20, 40 and 60 cm respectively. In the other dataset of 162 datapoints, 81 regular drip stains were formed from blood that had dripped passively from a subcutaneous syringe without needle at the aforementioned angle of impact and fall height, while the other stains were formed as a result of dripping of blood from a subcutaneous syringe with needle. In order to compare stains formed, all stains were recorded on the same representative, non-porous, smooth target surface under similar physical conditions. The interpretations relevant to the dataset are available in the article titled ‘2D Source Area prediction based on physical characteristics of a regular, passive blood drip stain’ (Basu and Bandyopadhyay, 2016) [7]. An image pre-processing algorithm for extracting ROI has also been incorporated in this article.

Blood Stain with Hammer Imprint Shown in Crime Scene

Like most other areas of Forensic Science, bloodstain pattern evidence interpretation is characterized by the overlap from various other fields of science such as physics, computer science, medical science etc. For example, fluid mechanics particularly explains the forces that lead to the formation of a particular bloodstain pattern. Forensic Medical practitioners particularly work towards drawing the correlation between the bloodstain patterns formed and the wound formed on the body or head of the victim concerned. The paper studied hammer transfer stains in particular because of the easy availability and usability of hammer round the world. Also we studied effect of stain pattern in the crime scene. The authors are of the view that of the different types of bloodstain patterns, the most common stain patterns visible at the crime scene, particularly in the case where the victim is found to suffer blunt force injuries, are saturation, impact, cast off and transfer stain patterns.