SHUTTLE will automate a significant part of forensic microtrace evidence examinations. The SHUTTLE toolkit will mainly consist of an automated microscope that will acquire high quality images of recovered microtraces. Images will be processed automatically and an overview of available microtraces will be reported. In first instance, we will focus on blood, skin cells, gunshot residues (especially NC), hairs, fibres and saliva. Algorithms to classify additional microtraces, or to classify microtraces more accurately can be developed by users and added as plug-ins to extend the range of microtraces that can be classified. The data will be stored in a computer database, thereby facilitating future data analysis, such as provenance of microtraces and forensic comparisons.

SHUTTLE aims to solve two major issues in forensic microtrace evidence investigation.

First, current analyses are subjective and require a high level of expertise and training of examiners. SHUTTLE will render analyses more objective and scientific. Second, microtrace evidence analyses are time consuming and hence expensive. This limits the number of cases in which analyses can be carried out.

Introduction of the SHUTTLE toolkit will have several advantages for forensic laboratories and their customers. The automation will allow a more efficient work flow, while the obtained results are more objective. The objective nature of the analyses and the available database will enable national or even international exchange of data.

Wide implementation of the SHUTTLE toolkit will homogenise the procedures for microtrace evidence examination in laboratories throughout Europe and hence facilitate better international collaboration and exchange of data. Laboratories may use data in a shared database for their database searches. In a similar way, data acquired by several laboratories can be used to calculate background populations and the calculation of the evidential value of the results. They may ask for help from international colleagues by just indicating a reference to the key under which data is stored in the joint database.

The standardisation of working procedures will form an excellent educational tool, as police officers and forensic can improve their knowledge by studying samples in the database. The SHUTTLE toolkit will also form a major incentive for Research and Development studies, e.g by enabling discrimination and background studies.


So far, all the trace analysis lean on the “Microscopist eyes”. It’s time-consuming, selective and hardly objective due to the complexity of the process.

The SHUTTLE toolkit will contain 4 tools which will help to solve the current difficulties. Each of them, 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 will include 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 will form the eyes of the SHUTTLE toolkit. It will 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 will be 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 will be operated using clear and intuive 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.
SHUTTLE process
  • Algorithms for image processing that will form the brain of the SHUTTLE toolkit. The algorithms will process the images acquired by the microscope and classify the different types of microtraces present in the tape. The results of the algorithms are 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 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 will form the memory of the SHUTTLE toolkit. This database will contain 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 will focus on experimental data and will (as is currently foreseen) not 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.

The aim is to make a powerful and versatile toolkit to solve the major issues in forensic microtrace evidence investigation. Additional specifications will be set on privacy issues, training, user-friendliness, long-term sustainability and integration with other techniques.