@InProceedings{piriyakumar:enhanced,
  author = {Douglas Antony Louis Piriyakumar and Paul Levi and Rolf
  Rabenseifner},
  title = {Enhanced File Interoperability with Parallel {MPI} File-{I/O} in
  Image Processing},
  booktitle = {Recent Advances in Parallel Virtual Machine and Message Passing
  Interface},
  year = {2002},
  series = {Lecture Notes in Computer Science},
  volume = {2474},
  pages = {174--?},
  publisher = {Springer-Verlag},
  URL =
  {http://link.springer.de/link/service/series/0558/bibs/2474/24740174.htm},
  URLpdf =
  {http://link.springer.de/link/service/series/0558/papers/2474/24740174.pdf},
  keywords = {parallel I/O, multiprocessor file system, pario-bib},
  abstract = {One of the crucial problems in image processing is Image
  Matching, i.e., to match two images, or in our case, to match a model with
  the given image. This problem being highly computation intensive, parallel
  processing is essential to obtain the solutions in time due to real world
  constraints. The Hausdorff method is used to locate human beings in images by
  matching the image with models and is parallelized with MPI. The images are
  usually stored in files with different formats. As most of the formats can be
  converted into ASCII file format containing integers, we have implemented 3
  strategies namely, Normal File Reading, Off-line Conversion and Run-time
  Conversion for free format integer file reading and writing. The
  parallelization strategy is optimized so that I/O overheads are minimal. The
  relative performances with multiple processors are tabulated for all the
  cases and discussed. The results obtained demonstrate the efficiency of our
  strategies and the implementations will enhance the file interoperability
  which will be useful for image processing community to use parallel systems
  to meet the real time constraints.}
}