Mr. Mario Hildebrandt Profile

Mario Hildebrandt

at Otto-von-Guericke-Univ Magdeburg

SPIE Involvement:

Author

Publications (21)

Proceedings Article | 4 March 2015 Paper

Benchmarking contactless acquisition sensor reproducibility for latent fingerprint trace evidence

Mario Hildebrandt, Jana Dittmann

Proceedings Volume 9409, 94090E (2015) https://doi.org/10.1117/12.2077637

KEYWORDS: Sensors, Biometrics, Printing, Feature extraction, Forensic science, Spectroscopy, Environmental sensing, Image resolution, Confocal microscopy, Colorimetry

Read Abstract +

Proceedings Article | 4 March 2015 Paper

Benford's Law based detection of latent fingerprint forgeries on the example of artificial sweat printed fingerprints captured by confocal laser scanning microscopes

Mario Hildebrandt, Jana Dittmann

Proceedings Volume 9409, 94090A (2015) https://doi.org/10.1117/12.2077531

KEYWORDS: Printing, Forensic science, Source mask optimization, Image processing, Confocal microscopy, Laser scanners, Microscopes, Pattern recognition, Data modeling, Sensors

Read Abstract +

Proceedings Article | 19 February 2014 Paper

An enhanced feature set for pattern recognition based contrast enhancement of contact-less captured latent fingerprints in digitized crime scene forensics

Mario Hildebrandt, Stefan Kiltz, Jana Dittmann, Claus Vielhauer

Proceedings Volume 9028, 902808 (2014) https://doi.org/10.1117/12.2039074

KEYWORDS: Biometrics, Image quality, Forensic science, Sensors, Visualization, Pattern recognition, Feature extraction, Data acquisition, Image enhancement, Source mask optimization

Read Abstract +

In crime scene forensics latent fingerprints are found on various substrates. Nowadays primarily physical or chemical preprocessing techniques are applied for enhancing the visibility of the fingerprint trace. In order to avoid altering the trace it has been shown that contact-less sensors offer a non-destructive acquisition approach. Here, the exploitation of fingerprint or substrate properties and the utilization of signal processing techniques are an essential requirement to enhance the fingerprint visibility. However, especially the optimal sensory is often substrate-dependent. An enhanced generic pattern recognition based contrast enhancement approach for scans of a chromatic white light sensor is introduced in Hildebrandt et al.¹ using statistical, structural and Benford's law² features for blocks of 50 micron. This approach achieves very good results for latent fingerprints on cooperative, non-textured, smooth substrates. However, on textured and structured substrates the error rates are very high and the approach thus unsuitable for forensic use cases. We propose the extension of the feature set with semantic features derived from known Gabor filter based exemplar fingerprint enhancement techniques by suggesting an Epsilon-neighborhood of each block in order to achieve an improved accuracy (called fingerprint ridge orientation semantics). Furthermore, we use rotation invariant Hu moments as an extension of the structural features and two additional preprocessing methods (separate X- and Y Sobel operators). This results in a 408-dimensional feature space. In our experiments we investigate and report the recognition accuracy for eight substrates, each with ten latent fingerprints: white furniture surface, veneered plywood, brushed stainless steel, aluminum foil, "Golden-Oak" veneer, non-metallic matte car body finish, metallic car body finish and blued metal. In comparison to Hildebrandt et al.,¹ our evaluation shows a significant reduction of the error rates by 15.8 percent points on brushed stainless steel using the same classifier. This also allows for a successful biometric matching of 3 of the 8 latent fingerprint samples with the corresponding exemplar fingerprint on this particular substrate. For contrast enhancement analysis of classification results we suggest to use known Visual Quality Indexes (VQI)³ as a contrast enhancement quality indicator and discuss our first preliminary results using the exemplary chosen VQI Edge Similarity Score (ESS),⁴ showing a tendency that higher image differences between a substrate containing a fingerprint and a substrate with a blank surface correlate with a higher recognition accuracy between a latent fingerprint and an exemplar fingerprint. Those first preliminary results support further research into VQIs as contrast enhancement quality indicator for a given feature space.

Proceedings Article | 22 March 2013 Paper

Visibility enhancement and validation of segmented latent fingerprints in crime scene forensics

Andrey Makrushin, Tobias Kiertscher, Mario Hildebrandt, Jana Dittmann, Claus Vielhauer

Proceedings Volume 8665, 866508 (2013) https://doi.org/10.1117/12.2003661

KEYWORDS: Forensic science, Image enhancement, Distance measurement, Sensors, Metals, Image filtering, Visualization, Image segmentation, Visibility, Image quality

Read Abstract +

Proceedings Article | 22 March 2013 Paper

Printed fingerprints at crime scenes: a faster detection of malicious traces using scans of confocal microscopes

Mario Hildebrandt, Stefan Kiltz, Jana Dittmann

Proceedings Volume 8665, 866509 (2013) https://doi.org/10.1117/12.2004507

KEYWORDS: Feature extraction, Microscopes, Confocal microscopy, Printing, Forensic science, Sensors, Source mask optimization, Image processing, Compact discs, Error analysis

Read Abstract +

Proceedings Article | 22 March 2013 Paper

Ballistic examinations based on 3D data: a comparative study of probabilistic Hough Transform and geometrical shape determination for circle-detection on cartridge bottoms

Robert Fischer, Claus Vielhauer, Mario Hildebrandt, Stefan Kiltz, Jana Dittmann

Proceedings Volume 8665, 86650F (2013) https://doi.org/10.1117/12.2004283

KEYWORDS: Hough transforms, Forensic science, Weapons, Firearms, Image processing, Microscopes, Image segmentation, Manufacturing, Confocal microscopy, Detection and tracking algorithms

Read Abstract +

The application of contact-less optical 3D sensing techniques yielding digital data for the acquisition of toolmarks on forensic ballistic specimens found at crime scenes, as well as the development of computer-aided, semi-automated firearm identification systems that are using 3D information, are currently emerging fields of research with rising importance. Traditionally, the examination of forensic ballistic specimen is done manually by highly skilled forensic experts using comparison microscopes. A partly automation of the comparison task promises examination results that are less dependent on subjective expertise and furthermore a reduction of the manual work needed. While there are some partly automated systems available they are all of proprietary nature to our current knowledge. One necessary requirement for the examination of forensic ballistic specimens is a reliable circle-detection and segmentation of cartridge bottoms. This information is later used for example for alignment and registration tasks, determination of regions of interest, and locally restricted application of complex feature-extraction algorithms. In this work we are using a Keyence VK-X 105 laser-scanning confocal microscope to acquire a very high detail topography image, a laserintensity image, and a color image of the assessed cartridge bottoms simultaneously. The work is focused on a comparison of Hough Transform (21HT) and Geometric Shape Determination for circle-detection on cartridge bottoms using 3D as well as 2D information. We compare the pre-processing complexity, the required processing time, and the ability for a reliable detection of all desired circles. We assume that the utilization of Geometric Shape Detection can reduce the required processing time due to a less complex processing. For application of shape determination as well as for Hough Transform we expect a more reliable circle-detection when using additional 3D information. Our first experimental evaluation, using 100 9mm center fire cartridges shot from 3 different firearms shows positive tendency to verify these suppositions.

Proceedings Article | 7 March 2013 Paper

Digitized forensics: retaining a link between physical and digital crime scene traces using QR-codes

Mario Hildebrandt, Stefan Kiltz, Jana Dittmann

Proceedings Volume 8667, 86670S (2013) https://doi.org/10.1117/12.2004548

KEYWORDS: Forensic science, Sensors, Process modeling, Digital forensics, Data acquisition, Mobile devices, Global Positioning System, Data modeling, Lab on a chip, Multimedia

Read Abstract +

Proceedings Article | 4 February 2013 Paper

Printing artificial sweat using ink jet printers for the test set generation in forensics: an image quality assessment of the reproducibility of the printing results

Mario Hildebrandt, Jennifer Sturm, Jana Dittmann

Proceedings Volume 8653, 86530O (2013) https://doi.org/10.1117/12.2004526

KEYWORDS: Printing, Forensic science, Feature extraction, Image quality, Compact discs, Confocal microscopy, Image processing, Statistical analysis, Crystals, Laser scanners

Read Abstract +

Proceedings Article | 4 May 2012 Paper

Advanced techniques for latent fingerprint detection and validation using a CWL device

Andrey Makrushin, Mario Hildebrandt, Robert Fischer, Tobias Kiertscher, Jana Dittmann, Claus Vielhauer

Proceedings Volume 8436, 84360V (2012) https://doi.org/10.1117/12.922235

KEYWORDS: Forensic science, Sensors, Metals, Statistical analysis, Ultraviolet radiation, Chemical analysis, Feature extraction, Data modeling, Visualization, Inspection

Read Abstract +

Proceedings Article | 2 May 2012 Paper

Environmental impact to multimedia systems on the example of fingerprint aging behavior at crime scenes

Ronny Merkel, Andy Breuhan, Mario Hildebrandt, Claus Vielhauer, Anja Bräutigam

Proceedings Volume 8436, 84360Y (2012) https://doi.org/10.1117/12.922701

KEYWORDS: Sensors, Humidity, Forensic science, Binary data, Environmental sensing, Temperature metrology, Multimedia, Feature extraction, Optical sensors, Image processing

Read Abstract +

Proceedings Article | 2 May 2012 Paper

Legally compatible design of digital dactyloscopy in future surveillance scenarios

Matthias Pocs, Maik Schott, Mario Hildebrandt

Proceedings Volume 8436, 84360Z (2012) https://doi.org/10.1117/12.921352

KEYWORDS: Computer security, Legal, Surveillance, Databases, Information technology, Control systems, Sensors, Data processing, Transparency, Information security

Read Abstract +

Proceedings Article | 2 May 2012 Paper

A first proposal for a general description model of forensic traces

Ina Lindauer, Martin Schäler, Claus Vielhauer, Gunter Saake, Mario Hildebrandt

Proceedings Volume 8436, 84360U (2012) https://doi.org/10.1117/12.922053

KEYWORDS: Databases, Forensic science, Data modeling, Weapons, Firearms, Colorimetry, Sensors, Optical sensors, Fingerprint recognition, Data acquisition

Read Abstract +

In recent years, the amount of digitally captured traces at crime scenes increased rapidly. There are various kinds of such traces, like pick marks on locks, latent fingerprints on various surfaces as well as different micro traces. Those traces are different from each other not only in kind but also in which information they provide. Every kind of trace has its own properties (e.g., minutiae for fingerprints, or raking traces for locks) but there are also large amounts of metadata which all traces have in common like location, time and other additional information in relation to crime scenes. For selected types of crime scene traces, type-specific databases already exist, such as the ViCLAS for sexual offences, the IBIS for ballistic forensics or the AFIS for fingerprints. These existing forensic databases strongly differ in the trace description models. For forensic experts it would be beneficial to work with only one database capable of handling all possible forensic traces acquired at a crime scene. This is especially the case when different kinds of traces are interrelated (e.g., fingerprints and ballistic marks on a bullet casing). Unfortunately, current research on interrelated traces as well as general forensic data models and structures is not mature enough to build such an encompassing forensic database. Nevertheless, recent advances in the field of contact-less scanning make it possible to acquire different kinds of traces with the same device. Therefore the data of these traces is structured similarly what simplifies the design of a general forensic data model for different kinds of traces. In this paper we introduce a first common description model for different forensic trace types. Furthermore, we apply for selected trace types from the well established database schema development process the phases of transferring expert knowledge in the corresponding forensic fields into an extendible, database-driven, generalised forensic description model. The trace types considered here are fingerprint traces, traces at locks, micro traces and ballistic traces. Based on these basic trace types, also combined traces (multiple or overlapped fingerprints, fingerprints on bullet casings, etc) and partial traces are considered.

Proceedings Article | 2 May 2012 Paper

Separation of high-resolution samples of overlapping latent fingerprints using relaxation labeling

Kun Qian, Maik Schott, Werner Schöne, Mario Hildebrandt

Proceedings Volume 8436, 84361A (2012) https://doi.org/10.1117/12.922696

KEYWORDS: Sensors, Image processing, Image sensors, Algorithm development, Independent component analysis, Colorimetry, Optical sensors, Statistical analysis, Optical properties, Imaging spectroscopy

Read Abstract +

Proceedings Article | 1 May 2012 Paper

Performance analysis of digital cameras versus chromatic white light (CWL) sensors for the localization of latent fingerprints in crime scenes

Mathias Jankow, Mario Hildebrandt, Jennifer Sturm, Stefan Kiltz, Claus Vielhauer

Proceedings Volume 8436, 84360X (2012) https://doi.org/10.1117/12.922550

KEYWORDS: Cameras, Sensors, Polarization, Image contrast enhancement, Feature extraction, Distortion, Printing, Image segmentation, Digital cameras, Colorimetry

Read Abstract +

In future applications of contactless acquisition techniques for latent fingerprints the automatic localization of potential fingerprint traces in crime scenes is required. Our goal is to study the application of a camera-based approach1 comparing with the performance of chromatic white light (CWL) techniques2 for the latent fingerprint localization in coarse and the resulting acquisition using detailed scans. Furthermore, we briefly evaluate the suitability of the camera-based acquisition for the detection of malicious fingerprint traces using an extended camera setup in comparison to Kiltz et al.3 Our experimental setup includes a Canon EOS 550D4 digital single-lens reflex (DSLR) camera and a FRT MicroProf2005 surface measurement device with CWL6002 sensor. We apply at least two fingerprints to each surface in our test set with 8 different either smooth, textured and structured surfaces to evaluate the detection performance of the two localization techniques using different pre-processing and feature extraction techniques. Printed fingerprint patterns as reproducible but potentially malicious traces3 are additionally acquired and analyzed on foil and compact discs. Our results indicate positive tendency towards a fast localization using the camera-based technique. All fingerprints that are located using the CWL sensor are found using the camera. However,the disadvantage of the camera-based technique is that the size of the region of interest for the detailed scan for each potential latent fingerprint is usually slightly larger compared to the CWL-based localization. Furthermore, this technique does not acquire 3D data and the resulting images are distorted due to the necessary angle between the camera and the surface. When applying the camera-based approach, it is required to optimize the feature extraction and classification. Furthermore, the required acquisition time for each potential fingerprint needs to be estimated to determine the time-savings of the camera-based localization approach throughout the entire acquisition of traces. The analysis of camera images of printed fingerprint patterns shows positive tendencies, too. However, only small sections of the fingerprint are sharply acquirable within a single photo, large sections of the image are usually blurred due to the depth of field of the camera lens.

Proceedings Article | 10 February 2012 Paper

Computer-aided fiber analysis for crime scene forensics

Mario Hildebrandt, Christian Arndt, Andrey Makrushin, Jana Dittmann

Proceedings Volume 8296, 829608 (2012) https://doi.org/10.1117/12.909852

KEYWORDS: Forensic science, Feature extraction, Sensors, Colorimetry, 3D image processing, Fiber characterization, Optical sensors, Machine learning, Structured optical fibers, Digital imaging

Read Abstract +

Proceedings Article | 9 February 2012 Paper

High-resolution printed amino acid traces: a first-feature extraction approach for fingerprint forgery detection

Mario Hildebrandt, Stefan Kiltz, Jennifer Sturm, Jana Dittmann, Claus Vielhauer

Proceedings Volume 8303, 83030J (2012) https://doi.org/10.1117/12.909072

KEYWORDS: Printing, Feature extraction, Forensic science, Sensors, Crystals, Statistical analysis, Biometrics, Edge detection, Algorithm development, Compact discs

Read Abstract +

Proceedings Article | 30 January 2012 Paper

3D imaging for ballistics analysis using chromatic white light sensor

Andrey Makrushin, Mario Hildebrandt, Jana Dittmann, Eric Clausing, Robert Fischer, Claus Vielhauer

Proceedings Volume 8290, 829016 (2012) https://doi.org/10.1117/12.908105

KEYWORDS: Firearms, Manufacturing, Databases, 3D image processing, Forensic science, Head, Stereoscopy, Feature extraction, Sensors, Imaging systems

Read Abstract +

Proceedings Article | 23 January 2012 Paper

AR.Drone: security threat analysis and exemplary attack to track persons

Fred Samland, Jana Fruth, Mario Hildebrandt, Tobias Hoppe, Jana Dittmann

Proceedings Volume 8301, 83010G (2012) https://doi.org/10.1117/12.902990

KEYWORDS: Information security, Video, Computer security, Network security, Control systems, Embedded systems, Cameras, Global Positioning System, Unmanned aerial vehicles, Information technology

Read Abstract +

Proceedings Article | 13 October 2011 Paper

Machine-assisted verification of latent fingerprints: first results for nondestructive contact-less optical acquisition techniques with a CWL sensor

Mario Hildebrandt, Stefan Kiltz, Dmytro Krapyvskyy, Jana Dittmann, Claus Vielhauer, Marcus Leich

Proceedings Volume 8189, 81890S (2011) https://doi.org/10.1117/12.897703

KEYWORDS: Feature extraction, Biometrics, Forensic science, Sensors, Nondestructive evaluation, Data acquisition, Visibility, Colorimetry, Optical sensors, Image resolution

Read Abstract +

Proceedings Article | 7 October 2011 Paper

Optical techniques: using coarse and detailed scans for the preventive acquisition of fingerprints with chromatic white-light sensors

Mario Hildebrandt, Jana Dittmann, Claus Vielhauer, Marcus Leich

Proceedings Volume 8187, 81870P (2011) https://doi.org/10.1117/12.897701

KEYWORDS: Glasses, Colorimetry, Feature extraction, Data acquisition, Sensors, Border security, Optical sensors, Forensic science, Analytical research, Nondestructive evaluation

Read Abstract +

Proceedings Article | 24 January 2011 Paper

Printed fingerprints: a framework and first results towards detection of artificially printed latent fingerprints for forensics

Stefan Kiltz, Mario Hildebrandt, Jana Dittmann, Claus Vielhauer, Christian Kraetzer

Proceedings Volume 7867, 78670U (2011) https://doi.org/10.1117/12.872329

KEYWORDS: Printing, Sensors, Forensic science, Carbon, Scanners, Digital cameras, Compact discs, Visibility, Statistical modeling, Optical resolution

Read Abstract +

Showing 5 of 21 publications

View contact details

UPDATE YOUR PROFILE

Is this your profile? Update it now.

Sign into your SPIE.org account

Don’t have a profile and want one?

Create an account on SPIE.org

Keywords/Phrases

Search In:

Publication Years