They highlighted two ways to fully utilize distributed computing in image processing which are task and data parallelism.
Computing intensive image processing, sharing/workflows and archiving are the three major application areas, security the major challenge.
In addition to these categories, the documents are classified into eight different sub-domains, which are databases, computational intelligence, software engineering, hypermedia, digital systems, distributed systems, and concurrent programming, graphical computing and image processing, and high-performance computing.
However, observations by an expert can be very time consuming and error prone when there are a large number of potential areas of interest (such as cells or vessels in a tumour), and compute intensive image processing is required to analyse them.
Cellular neural networks proved to be a useful parallel computing system for image processing applications.
On the other hand, GPU is a well-known parallel computing platform for image processing.
Airspaces Number (AN), covered area (AA) and dimensions (AD) were computed by using the Image Processing Toolbox for MatLab (Mathworks, Natick, USA).
Numerosity (N), total area (A), and Area/Numerosity ratio (A/N) indexes were computed by using the Image Processing Toolbox for MatLab (Mathworks, Natick, USA).
The mixing experiments were performed using phenolphthalein and NaOH solution, and the mixing time was computed using a simple image processing algorithm to track intensity changes implemented in MATLAB.
The system combines optical sensing, digital image processing and computing techniques and is designed to measure most physical parameters of a flame.
