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  • 1.
    Astrom, Anders
    et al.
    Combitech AB, Linköping, Sweden .
    Forchheimer, Robert
    Linköping University, Department of Electrical Engineering, Information Coding. Linköping University, The Institute of Technology.
    Low-complexity, high-speed, and high-dynamic range time-to-impact algorithm2012In: Journal of Electronic Imaging (JEI), ISSN 1017-9909, E-ISSN 1560-229X, Vol. 21, no 4Article in journal (Refereed)
    Abstract [en]

    We present a method suitable for a time-to-impact sensor. Inspired by the seemingly "low" complexity of small insects, we propose a new approach to optical flow estimation that is the key component in time-to-impact estimation. The approach is based on measuring time instead of the apparent motion of points in the image plane. The specific properties of the motion field in the time-to-impact application are used, such as measuring only along a one-dimensional (1-D) line and using simple feature points, which are tracked from frame to frame. The method lends itself readily to be implemented in a parallel processor with an analog front-end. Such a processing concept [near-sensor image processing (NSIP)] was described for the first time in 1983. In this device, an optical sensor array and a low-level processing unit are tightly integrated into a hybrid analog-digital device. The high dynamic range, which is a key feature of NSIP, is used to extract the feature points. The output from the device consists of a few parameters, which will give the time-to-impact as well as possible transversal speed for off-centered viewing. Performance and complexity aspects of the implementation are discussed, indicating that time-to-impact data can be achieved at a rate of 10 kHz with todays technology.

  • 2.
    Gooran, Sasan
    et al.
    Linköping University, Department of Science and Technology, Media and Information Technology. Linköping University, The Institute of Technology.
    Kruse, Björn
    Linköping University, Department of Science and Technology, Media and Information Technology. Linköping University, The Institute of Technology.
    High-speed first- and second-order frequency modulated halftoning2015In: Journal of Electronic Imaging (JEI), ISSN 1017-9909, E-ISSN 1560-229X, Vol. 24, no 2Article in journal (Refereed)
    Abstract [en]

    Halftoning is a crucial part of image reproduction in print. First-order FM halftones, in which the single dots are stochastically distributed, is widely used in printing technologies, such as inkjet, that are able to stably print isolated dispersed dots. Printers, such as laser printers, that utilize electrophotographic technology are not able to stably print the isolated dots and therefore use clustered-dot halftones. Periodic clustered-dot, i.e. AM, halftones are commonly used in this type of printers but they suffer from undesired periodic interference pattern called moiré. An alternative solution is to use second-order FM halftones in which the clustered dots are stochastically distributed. The iterative halftoning techniques, that usually result in well-formed halftones, are operating on the whole input image and require extensive computations and thereby are very slow when the input image is large. In this paper, we introduce a method to generate image independent threshold matrices for first and second-order FM halftoning. The first-order threshold matrix generates well-formed halftone patterns and the second-order FM threshold matrix can be adjusted to produce clustered-dots of different size, shape and alignment. Using predetermined and image independent threshold matrices makes the proposed halftoning method a point-by-point process and thereby very fast.

  • 3.
    Nawaz, Tahir
    et al.
    Computational Vision Group, Department of Computer Science, University of Reading.
    Berg, Amanda
    Linköping University, Department of Electrical Engineering, Computer Vision. Linköping University, Faculty of Science & Engineering. Termisk Systemteknik AB, Linköping, Sweden.
    Ferryman, James
    Computational Vision Group, Department of Computer Science, University of Reading.
    Ahlberg, Jörgen
    Linköping University, Department of Electrical Engineering, Computer Vision. Linköping University, Faculty of Science & Engineering. Termisk Systemteknik AB, Linköping, Sweden.
    Felsberg, Michael
    Linköping University, Department of Electrical Engineering, Computer Vision. Linköping University, Faculty of Science & Engineering.
    Effective evaluation of privacy protection techniques in visible and thermal imagery2017In: Journal of Electronic Imaging (JEI), ISSN 1017-9909, E-ISSN 1560-229X, Vol. 26, no 5, article id 051408Article in journal (Refereed)
    Abstract [en]

    Privacy protection may be defined as replacing the original content in an image region with a new (less intrusive) content having modified target appearance information to make it less recognizable by applying a privacy protection technique. Indeed the development of privacy protection techniques needs also to be complemented with an established objective evaluation method to facilitate their assessment and comparison. Generally, existing evaluation methods rely on the use of subjective judgements or assume a specific target type in image data and use target detection and recognition accuracies to assess privacy protection. This work proposes a new annotation-free evaluation method that is neither subjective nor assumes a specific target type. It assesses two key aspects of privacy protection: protection and utility. Protection is quantified as an appearance similarity and utility is measured as a structural similarity between original and privacy-protected image regions. We performed an extensive experimentation using six challenging datasets (having 12 video sequences) including a new dataset (having six sequences) that contains visible and thermal imagery. The new dataset, called TST-Priv, is made available online below for community. We demonstrate effectiveness of the proposed method by evaluating six image-based privacy protection techniques, and also show comparisons of the proposed method over existing methods.

  • 4. Zhukov, L
    et al.
    Museth, Ken
    Linköping University, Department of Science and Technology, Digital Media. Linköping University, The Institute of Technology.
    Breen, David
    Whitaker, Ross
    Barr, A
    Level Set Segmentation and Modeling of DT-MRI human brain data2003In: Journal of Electronic Imaging (JEI), ISSN 1017-9909, E-ISSN 1560-229X, Vol. 12, no 1, p. 125-133Article in journal (Refereed)
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