Dr. Christian Merfort Profile

Dr. Christian Merfort

Business Development Manager at Everlight Electronics Europe GmbH

SPIE Involvement:

Author

Area of Expertise:

optoelectronic sensor development , microsystem technologies , colorimetry , multivariate analysis , civil security applications , material detection

Websites:

Personal Website

Publications (6)

Proceedings Article | 13 June 2014 Paper

Proper spectral band adjustment for coloristic feature-based recognition of safety signs

Christian Merfort, Daniel Schneider, Markus Boehm

Proceedings Volume 9088, 90881C (2014) https://doi.org/10.1117/12.2049594

KEYWORDS: Safety, RGB color model, Digital filtering, Image filtering, Tolerancing, Information security, Environmental sensing, Optical filters, Color reproduction, Image sensors

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SPIE Journal Paper | 8 April 2013

Target recognitions in multiple-camera closed-circuit television using color constancy

Umair Soori, Peter Yuen, Ji Wen Han, Izzati Ibrahim, Wentao Chen, Kan Hong, Christian Merfort, Mark Richardson, David James

OE, Vol. 52, Issue 04, 047202, (April 2013) https://doi.org/10.1117/12.10.1117/1.OE.52.4.047202

KEYWORDS: Target detection, Cameras, Detection and tracking algorithms, Target recognition, Video, Data processing, Televisions, Sensors, RGB color model, Optical engineering

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People tracking in crowded scenes from closed-circuit television (CCTV) footage has been a popular and challenging task in computer vision. Due to the limited spatial resolution in the CCTV footage, the color of people’s dress may offer an alternative feature for their recognition and tracking. However, there are many factors, such as variable illumination conditions, viewing angles, and camera calibration, that may induce illusive modification of intrinsic color signatures of the target. Our objective is to recognize and track targets in multiple camera views using color as the detection feature, and to understand if a color constancy (CC) approach may help to reduce these color illusions due to illumination and camera artifacts and thereby improve target recognition performance. We have tested a number of CC algorithms using various color descriptors to assess the efficiency of target recognition from a real multicamera Imagery Library for Intelligent Detection Systems (i-LIDS) data set. Various classifiers have been used for target detection, and the figure of merit to assess the efficiency of target recognition is achieved through the area under the receiver operating characteristics (AUROC). We have proposed two modifications of luminance-based CC algorithms: one with a color transfer mechanism and the other using a pixel-wise sigmoid function for an adaptive dynamic range compression, a method termed enhanced luminance reflectance CC (ELRCC). We found that both algorithms improve the efficiency of target recognitions substantially better than that of the raw data without CC treatment, and in some cases the ELRCC improves target tracking by over 100% within the AUROC assessment metric. The performance of the ELRCC has been assessed over 10 selected targets from three different camera views of the i-LIDS footage, and the averaged target recognition efficiency over all these targets is found to be improved by about 54% in AUROC after the data are processed by the proposed ELRCC algorithm. This amount of improvement represents a reduction of probability of false alarm by about a factor of 5 at the probability of detection of 0.5. Our study concerns mainly the detection of colored targets; and issues for the recognition of white or gray targets will be addressed in a forthcoming study.

Proceedings Article | 24 May 2012 Paper

Application specific band selection with multivariate methods of analysis for a-Si:H multispectral photodiodes

Christian Merfort, Andreas Bablich, Oliver Schwaneberg, Krystian Watty, Markus Boehm

Proceedings Volume 8390, 839024 (2012) https://doi.org/10.1117/12.918456

KEYWORDS: Sensors, Photodiodes, Reliability, Light sources, Fuzzy logic, Chlorine, Virtual reality, Reflectivity, Clouds, Principal component analysis

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Proceedings Article | 19 May 2012 Paper

FIB-assisted a-SiGe:H/a-SiC:H alloy analysis for ultra-low biased multispectral pixn sensors with enhanced color separation features and low-reflective ZnO:Al back-contacts

Andreas Bablich, Krystian Watty, Christian Merfort, Markus Böhm

Proceedings Volume 8376, 83760Q (2012) https://doi.org/10.1117/12.918318

KEYWORDS: Sensors, Absorption, Reflectivity, Photons, Diodes, Visible radiation, Amorphous silicon, Thin films, Photodiodes, Chromium

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Proceedings Article | 19 May 2012 Paper

Novel approach to improve reliable color recognition in a-Si:H photodiodes

Krystian Watty, Andreas Bablich, Konstantin Seibel, Christian Merfort, Markus Böhm

Proceedings Volume 8376, 83760N (2012) https://doi.org/10.1117/12.918566

KEYWORDS: Photodiodes, Diodes, Transparent conductors, Amorphous silicon, Photonic devices, Absorption, Quantum efficiency, Silicon, Sensors, Deposition processes

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Proceedings Article | 6 October 2011 Paper

The top down design flow of a-Si:H photodiodes with multivariate methods of analysis

Christian Merfort, Andreas Bablich, Oliver Schwaneberg, Krystian Watty, Markus Böhm

Proceedings Volume 8186, 81860N (2011) https://doi.org/10.1117/12.897374

KEYWORDS: Sensors, Photodiodes, Light sources, Chlorine, Silicon, Reflectivity, Principal component analysis, Diodes, Eye, Absorption

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Showing 5 of 6 publications

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