License plate recognition (LPR) algorithms in images or videos are generally composed of the following three processing steps: 1) extraction of a license plate region; 2) segmentation of the plate characters; and 3) recognition of each character This task is quite challenging due to the diversity of plate formats and the nonuniform outdoor illumination conditions during image acquisition Therefore, most approaches work only under restricted conditions such as fixed illumination, limited vehicle speed, designated routes, and stationary backgrounds Numerous techniques have been developed for LPR in still images or video sequences, and the purpose of this paper is to categorize and assess them Issues such as processing time, computational power, and recognition rate are also addressed, when available Finally, this paper offers to researchers a link to a public image database to define a common reference point for LPR algorithmic assessment

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License Plate Recognition From Still Images and Video Sequences: A Survey

The potential of virtual environments for teaching people with autism has been positively promoted in recent years. The present study aimed to systematically investigate this potential with 12 participants with autistic spectrum disorders (ASDs), each individually matched with comparison participants according to either verbal IQ or performance IQ, as well as gender and chronological age. Participants practised using a desktop 'training' virtual environment, before completing a number of tasks in a virtual cafe. We examined time spent completing tasks, errors made, basic understanding of the representational quality of virtual environments and the social appropriateness of performance. The use of the environments by the participants with ASDs was on a par with their PIQ-matched counterparts, and the majority of the group seemed to have a basic understanding of the virtual environment as a representation of reality. However, some participants in the ASD group were significantly more likely to be judged as bumping into, or walking between, other people in the virtual scene, compared to their paired matches. This tendency could not be explained by executive dysfunction or a general motor difficulty. This might be a sign that understanding personal space is impaired in autism. Virtual environments might offer a useful tool for social skills training, and this would be a valuable topic for future research.

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The use and understanding of virtual environments by adolescents with autistic spectrum disorders.

Previous research has shown that even low end-to-end latency can have adverse effects on performance in virtual environments (VE). This paper reports on an experiment investigating the effect of latency on other metrics of VE effectiveness: physiological response, simulator sickness, and self-reported sense of presence. The VE used in the study includes two rooms: the first is normal and non-threatening; the second is designed to evoke a fear/stress response. Participants were assigned to either a low latency (/spl sim/50 ms) or high latency (/spl sim/90 ms) group. Participants in the low latency condition had a higher self-reported sense of presence and a statistically higher change in heart rate between the two rooms than did those in the high latency condition. There were no significant relationships between latency and simulator sickness.

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Effect of latency on presence in stressful virtual environments

Image Fusion Algorithm Based on Spatial Frequency-Motivated Pulse Coupled Neural Networks in Nonsubsampled Contourlet Transform Domain

Several virtual reality (VR) applications for the understanding, assessment and treatment of mental health problems have been developed in the last 10 years. The purpose of this review is to outline the current state of virtual reality research in the treatment of mental health problems. PubMed and PsycINFO were searched for all articles containing the words “virtual reality”. In addition a manual search of the references contained in the papers resulting from this search was conducted and relevant periodicals were searched. Studies reporting the results of treatment utilizing VR in the mental health field and involving at least one patient were identified. More than 50 studies using VR were identified, the majority of which were case studies. Seventeen employed a between groups design: 4 involved patients with fear of flying; 3 involved patients with fear of heights; 3 involved patients with social phobia/public speaking anxiety; 2 involved people with spider phobia; 2 involved patients with agoraphobia; 2 involved patients with body image disturbance and 1 involved obese patients. There are both advantages in terms of delivery and disadvantages in terms of side effects to using VR. Although virtual reality based therapy appears to be superior to no treatment the effectiveness of VR therapy over traditional therapeutic approaches is not supported by the research currently available. There is a lack of good quality research on the effectiveness of VR therapy. Before clinicians will be able to make effective use of this emerging technology greater emphasis must be placed on controlled trials with clinically identified populations.

Virtual reality in mental health : a review of the literature.

Pulse coupled neural network (PCNN) models are described. The linking field modulation term is shown to be a universal feature of any biologically grounded dendritic model. Applications and implementations of PCNNs are reviewed. Application based variations and simplifications are summarized. The PCNN image decomposition (factoring) model is described in detail.

PCNN models and applications

In just the past decade virtual environment (VE) applications have emerged in entertainment,
training, education, and other areas (see Chapters 43-55, this volume). In that time extensive
research in VE technology has also been conducted. However, the terminology used to characterize this technology is still evolving. In fact, Durlach and Mavor (1995, p. 2) indicate that
“inadequate terminology [is] being used” to describe VE technology and its applications. It is
thus important to describe the key terms that are used in this handbook. The objective is not to
resolve differences between disparate uses (in fact often multiple, even conflicting definitions
are presented) but rather to provide a coherent set of commonly used terms. While it is customary to present a glossary at the end of handbooks such as this one, this work starts out with
a glossary so that readers may develop a common understanding of the terms used throughout
the handbook. Paradoxically, the one term that remains particularly elusive is virtual environment. Many authors, especially those among the application chapters (see chaps. 43-55,
this volume) have catered the definition of VE to fit the forms of the technology that best
suit their needs. Perhaps this definitional multiplicity demonstrates the versatile nature of VE
technology and its wide array of potential uses.

Mary Lou Padgett

Papers

PCNN models and applications

Virtual Environments Standards and Terminology

Virtual Environments: History and Profession.