Content-Based Image Recognition with Cellular Discrete-Event System Specifications

Context-aware application development for mobile systems is a new trend in ubiquitous computing systems research. The idea is to capitalize on contextual data (i.e. user loca-tion, time of day, nearby facilities and people, user activity, etc.) in order to satisfy user-specific needs and offering rel-evant data and services to the audience. Here, we show hoe to use the Cell-DEVS methodology to apply intelligent ob-ject recognition algorithms to solve the above research questions. The cellular nature of the modeling approach and the rule-base behavior definition for cells provides a platform for pixel-wise operations, leading to easier and faster adoption and implementation of content-based algorithms. The other advantage of this method is its fast computing apparatus working asynchronously on the cellular grid, increasing the execution speed.

@Conference_Paper\{MW12,
  author       = "Moallemi, Mohammad and Wainer, Gabriel A.",
  title        = "Content-Based Image Recognition with Cellular Discrete-Event System Specifications",
  category     = "Cellular Modeling Techniques",
  video        = "http://www.youtube.com/watch?v=b4bhaJYmdCU",
  booktitle    = "Proceedings of 2012 Spring Simulation Conference (SpringSim12), ANSS Symposium",
  month        = "March",
  year         = "2012",
  publisher    = "ACM",
  organization = "Society for Modeling and Simulation International (SCS)",
  address      = "Orlando, FL",
  note         = "Work-In-Progress",
  keywords     = "Cell-DEVS, Real-Time, Content-Based, Image-Recognition",
  url          = "http://cell-devs-02.sce.carleton.ca/publications/2012/MW12"
}