Quantifying the similarity of 2D images using edge pixels: an application to the forensic comparison of footwear impressions

We propose a novel method to quantify the similarity between an impression (Q) from an unknown source and a test impression (K) from a known source. Using the property of geometrical congruence in the impressions, the degree of correspondence is quantified using ideas from graph theory and maximum clique (MC). The algorithm uses the x and y coordinates of the edges in the images as the data. We focus on local areas in Q and the corresponding regions in K and extract features for comparison. Using pairs of images with known origin, we train a random forest to classify pairs into mates and non-mates. We collected impressions from 60 pairs of shoes of the same brand and model, worn over six months. Using a different set of very similar shoes, we evaluated the performance of the algorithm in terms of the accuracy with which it correctly classified images into source classes. Using classification error rates and ROC curves, we compare the proposed method to other algorithms in the literature and show that for these data, our method shows good classification performance relative to other methods. The algorithm can be implemented with the R package shoeprintr

Quantitative assessment of the discrimination potential of class and randomly acquired characteristics for crime scene quality shoeprints

Footwear evidence has tremendous forensic value; it can focus a criminal investigation, link suspects to scenes, help reconstruct a series of events, or otherwise provide information vital to the successful resolution of a case. When considering the specific utility of a linkage, the strength of the connection between the source footwear and an impression left at the scene of a crime varies with the known rarity of the shoeprint itself, which is a function of the class characteristics, as well as the complexity, clarity, and quality of randomly acquired characteristics (RACs) available for analysis. To help elucidate the discrimination potential of footwear as a source of forensic evidence, the aim of this research was three-fold.;The first (and most time consuming obstacle) of this study was data acquisition. In order to efficiently process footwear exemplar inputs and extract meaningful data, including information about randomly acquired characteristics, a semi-automated image processing chain was developed. To date, 1,000 shoes have been fully processed, yielding a total of 57,426 RACs characterized in terms of position (theta, r, rnorm), shape (circle, line/curve, triangle, irregular) and complex perimeter (e.g., Fourier descriptor). A plot of each feature versus position allowed for the creation of a heat map detailing coincidental RAC co-occurrence in position and shape. Results indicate that random chance association is as high as 1:756 for lines/curves and as low as 1:9,571 for triangular-shaped features. However, when a detailed analysis of the RAC\u27s geometry is evaluated, each feature is distinguishable.;The second goal of this project was to ascertain the baseline performance of an automated footwear classification algorithm. A brief literature review reveals more than a dozen different approaches to automated shoeprint classification over the last decade. Unfortunately, despite the multitude of options and reports on algorithm inter-comparisons, few studies have assessed accuracy for crime-scene-like prints. To remedy this deficit, this research quantitatively assessed the baseline performance of a single metric, known as Phase Only Correlation (POC), on both high quality and crime-scene-like prints. The objective was to determine the baseline performance for high quality exemplars with high signal-to-noise ratios, and then determine the degree to which this performance declined as a function of variations in mixed media (blood and dust), transfer mechanisms (gel lifters), enhancement techniques (digital and chemical) and substrates (ceramic tiles, vinyl tiles, and paper). The results indicate probabilities greater than 0.850 (and as high as 0.989) that known matches will exhibit stochastic dominance, and probabilities of 0.99 with high quality exemplars (Handiprints or outsole edge images).;The third and final aim of this research was to mathematically evaluate the frequency and similarity of RACs in high quality exemplars versus crime-scene-like impressions as a function of RAC shape, perimeter, and area. This was accomplished using wet-residue impressions (created in the laboratory, but generated in a manner intended to replicate crime-scene-like prints). These impressions were processed in the same manner as their high quality exemplar mates, allowing for the determination of RAC loss and correlation of the entire RAC map between crime scene and high quality images. Results show that the unpredictable nature of crime scene print deposition causes RAC loss that varies from 33-100% with an average loss of 85%, and that up to 10% of the crime scene impressions fully lacked any identifiable RACs. Despite the loss of features present in the crime-scene-like impressions, there was a 0.74 probability that the actual shoe\u27s high quality RAC map would rank higher in an ordered list than a known non-match map when queried with the crime-scene-like print. Moreover, this was true despite the fact that 64% of the crime-scene-like impressions exhibit 10 or fewer RACs

If the Shoe Fits: Proposing a Randomised Control Trial on the effect of a digitised in-custody footwear technology compared to a paper-based footwear method.

In order to address the issue of footwear capture from individuals arrested for recordable crime, technology has been developed, which is known as Tread Finder. This technology and development was made possible through Home Office Police Innovation Funding. Tread Finder is now a finished product and the technology has been deployed into a North London custody suite. Tread Finder incorporates the use of a 300 dpi scanner and newly developed software enabling capture, assisted coding and automated geographical crime scene searching. This paper sets out the proposal of a Randomised Control Trial to replicate and upscale a previous lab based experiment into a field environment to assess the cost, efficiency and crime solving benefits realised as a result of deploying Tread Finder technology compared with the previous paper based alternative

The Methodological Issues of the C.S.I Effect and it’s Controversial Impact on Criminal Investigation

With the rising success of crime-scene related television shows in recent years, and forensic science as a new hot topic in multiple settings, the world of criminal justice faces new complications as this phenomenon continues to grow. This is popularly known as “The C.S.I Effect.” Contrary to belief, much of what the public perceives, or think they know about the operations of law enforcement and the legal system, comes from television. Consequently, as these television programs appeal to greater audiences around the world, increasingly unreasonable expectations are established in the forensic world, both inside and out of the courtroom. In light of this issue, research has discussed the many television shows that have greatly influenced the public perception such as C.S.I, Dexter and Sherlock, and provides a myriad of examples, describing the inconsistencies and flaws that these shows are able to portray in the span of a 40-minute program time slot. With each example, the correct methods, linguistics and techniques that are used in real-world investigations will be explained and the efficiency they provide to criminal cases. Throughout this research, the extension of the C.S.I Effect will be discussed, as well as its impact on a student’s decision in choosing a major in Forensic Science- are they truly satisfied with their choice or disappointed by the reality? Comparative analysis of the C.S.I Effect in the courtroom will be presented, as well as the controversy behind such a theory, will also be discussed at length. The goal of this research is to determine any empirical evidence behind the commonly-held belief that juror expectations for forensic evidence are linked to watching law-related television shows and if there can or cannot be anything to fix this detrimental issue

An algorithm to compare two‐dimensional footwear outsole images using maximum cliques and speeded‐up robust feature

Footwear examiners are tasked with comparing an outsole impression (Q) left at a crime scene with an impression (K) from a database or from the suspect\u27s shoe. We propose a method for comparing two shoe outsole impressions that relies on robust features (speeded‐up robust feature; SURF) on each impression and aligns them using a maximum clique (MC). After alignment, an algorithm we denote MC‐COMP is used to extract additional features that are then combined into a univariate similarity score using a random forest (RF). We use a database of shoe outsole impressions that includes images from two models of athletic shoes that were purchased new and then worn by study participants for about 6 months. The shoes share class characteristics such as outsole pattern and size, and thus the comparison is challenging. We find that the RF implemented on SURF outperforms other methods recently proposed in the literature in terms of classification precision. In more realistic scenarios where crime scene impressions may be degraded and smudged, the algorithm we propose—denoted MC‐COMP‐SURF—shows the best classification performance by detecting unique features better than other methods. The algorithm can be implemented with the R‐package shoeprintr

The significance of efficient murder crime scene processing

This study sought to explore the significance of efficient murder crime scene processing. Data were collected through semi-structured interviews conducted with investigators who investigate murder cases in the Nyanga South African Police Service (SAPS) cluster in the Western Cape, to stimulate knowledge of the significance of efficient murder scene processing. A literature study relating to aspects of crime scene management and crime scene processing was conducted. From the results of this research, it appears that participants did realise the significance of efficient murder scene processing. It is, however, apparent that they experienced challenges and shortcomings with regard to efficiently processing murder scenes. Reasons for this are inexperienced investigators, overload of murder scenes to investigate, lack of human resources, and lack of cooperation between investigators and crime scene experts. The study makes recommendations that could assist the Nyanga SAPS cluster in improving the processing of murder scenes.Police PracticeM. Tech. (Forensic Investigation

Development of a method to recover fingerprints from textured surfaces

Latent fingerprints have a high evidentiary value but are currently being underutilized from textured surfaces like dashboards. There is no current method to lift latent fingerprints from a textured surface. Dashboards are the principal surfaces for several crime types, and being able to lift fingerprints from their surfaces would help investigators. The problem with dashboards is the textured nature of their surface prevents the current methods from working. Enhancement methods looked at is the powder type used for initial enhancement. A lifter or casting material could be used to detach the print from the surface without texture affecting the fingerprint. It was noted that after lifting, the fingerprint would not have high contrast with the surface, so cyanoacrylate fuming and dyed with rhodamine 6G would happen to increase contrast, both cyanoacrylate fuming and rhodamine 6G both works used extensively for current methods to enhance contrast. Lifters and casting materials were neither research in there use for and results on textured surfaces and should be researched more extensively

Technological innovations in the collection and analysis of three-dimensional footwear impression evidence.

The development of digital 3D trace recovery in the fields of geology and archaeology has highlighted transferable methods that could be used for the recovery of 3D footwear impressions under the umbrella of forensic science. This project uses a portfolio of experiments and case studies to explore the veracity and application of SfM Photogrammetry (i.e., DigTrace) within forensic footwear. This portfolio-based research includes published papers integrated into conventional chapters. A method of comparing the accuracy and precision of different measurement methods is developed and introduced and gives a comparative view of multiple recovery techniques. A range of simulated crime scene and laboratory-controlled experiments have been conducted to compare different recovery methods such as casting, photography and SfM photogrammetry. These have been compared for accuracy, practicality and effectiveness. In addition, a range of common and lesser common footwear bearing substrates have been compared using SfM as well as other methods. One of the key findings shows that DigTrace SfM photogrammetry software reliably produces accurate forensic results, regardless of the camera used for initial photography and in a multitude of environments. This includes but is not limited to, soil, sand, snow, and other less obvious substrates such as food items, household items and in particular carpet. The thesis also shows that SfM photogrammetry provides a superior solution in the recovery of ‘difficult to cast’ footwear impressions. This finding allows for 3D recovery of impressions that would otherwise have only been photographed in 2D. More generally this project shows that 3D recovery is preferential to 2D and aids in the identification of individual characteristics and subsequent positive analysis. Overall, the thesis concludes that SfM photogrammetry is a viable and accurate solution for the recovery of 3D footwear impressions both as an alternative and replacement to 2D photography and conventional 3D casting. SfM 3D recovery provides increased visualisation of footwear evidence and individualising marks. Digital evidence obtained in this way integrates with the increasingly sophisticated search algorithms being used within the UK’s National Footwear Database and allows rapid file sharing, retrieval and evidence sharing. Moreover, the technique has significant cost saving in terms of time, equipment and resources. It is the author’s opinion, having consulted a wide audience of footwear examiners and crime scene employees, that this technique should, and can be, adopted quickly by forces in the UK and USA and disseminated for use