The SHUTTLE toolkit was designed to contain 4 tools. Each of these tools, as well as their fluent interaction, is required for optimal operation.
- Microscopic grade tape. Tapes have been used to recover microtraces for several decades. Their popularity is based on easy handling, low cost, and efficiency for many types of microtraces. A current disadvantage of tapes is that microscopic images acquired through tapes do not yield optimal image quality. Therefore, relevant microtraces are often transferred into glass slides to improve image quality. The tender included the supply or development of a tape that allows imaging quality comparable to glass slides and facilitate analysis on surfaces much larger than can be achieved by standard glass slides.
- An automated microscope that forms the eyes of the SHUTTLE toolkit. The aim was to acquire high quality images of microtraces that have been recovered using the developed tapes. The microscope will use a number of illumination modes for optimal discrimination and classification of microtraces. The microscope allows spectrometric colour analysis. The classification is aided by advanced polarisation analysis. The required spatial resolution is moderate, but the total field of view is large, while acquisition time must be acceptable. The SHUTTLE microscope uses a clear and intuitive software. The software allows the definition of a standard analysis procedure. In addition, there is a feature for advanced users that allows data acquisition using non-standard parameters.
- Algorithms for image processing that form the brain of the SHUTTLE toolkit. The algorithms process the images acquired by the microscope and classify the different types of microtraces present in the tape. The results of the algorithms is a table that contains a number of parameter vectors for every microtrace, such as the coordinates on the tape, the colour, polarisation characteristics, morphology, and class (e.g. ‘blood’, ‘fibre’, ‘glass’, etc.). These algorithms can be executed via a GUI (graphical user interface). Via this GUI, users can execute the algorithms developed within the SHUTTLE project. In addition, the can develop and share additional algorithms and plug them into the the GUI. Such additional algorithms may serve to classify additional microtraces, or to make a better subclassification. As an example, the SHUTTLE toolkit might classify a microtrace as a ‘hair’, while additional algorithms can discriminate and classify ‘scalp hairs, ‘pubic hairs’, ‘body hair’, or even discriminate hairs from different animals.
- A database and search algorithms, that form the memory of the SHUTTLE toolkit. This database contains the data (raw, processed or both) acquired by the microscope and processed by the image processing algorithms. The database structure is made in such a way that the data acquired by the SHUTTLE toolkit can be related to data acquired by other techniques. To achieve this, it is possible to add into the database parts that contain data from e.g. FTIR, MSP, dye analysis, etc. The database contains a robust back-end and a user-friendly front-end. The front-end should have the same look and feel as (or even be integrated with) those for instrument and the image processing routines. The database focuses on experimental data and was not expected to contain case information (such as case identifiers, names of suspects and victims) to prevent security and privacy issues. The search algorithms should allow searches for similar samples in the database. The search algorithms yield numbers or probabilities that can be used to calculate the evidential value of a result, e.g. using Bayesian statistics.
We aim to make the SHUTTLE toolkit powerful and versatile to such an extent, that it will become an international standard in forensic microtrace evidence examination. Therefore, the specifications not only covered the technical aspects. Additional specifications were set on privacy issues, training, user-friendliness, long-term sustainability, and integration with other techniques.
