ANNOUNCEMENT: Parallel Algorithms for Image Enhancement and Segmentation

ANNOUNCEMENT: Parallel Algorithms for Image Enhancement and Segmentation

Post by David Bad » Sun, 14 May 1995 04:00:00



ANNOUNCEMENT:

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Parallel Algorithms for Image Enhancement and Segmentation by
       Region Growing with an Experimental Study
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We have released our technical report entitled ``Parallel Algorithms
for Image Enhancement and Segmentation by Region Growing with an
Experimental Study,'' by David A. Bader, Joseph Ja'Ja', David Harwood,
and Larry S. Davis. Technical Report Number: CS-TR-3449 and
UMIACS-TR-95-44. Institute for Advanced Computer Studies (UMIACS),
University of Maryland, College Park, May 1995.

The paper is available in HTML and PostScript format via WWW:

http://www.umiacs.umd.edu/~dbader

or via anonymous ftp to:

ftp://ftp.cs.umd.edu/pub/papers/papers/3449/3449.ps.Z

If you prefer a hardcopy, please reply to this message and send me
your mailing address.

ABSTRACT:
     This paper presents efficient and portable implementations of a
   useful image enhancement process, the Symmetric Neighborhood Filter
   (SNF), and an image segmentation technique which makes use of the SNF
   and a variant of the conventional connected components algorithm which
   we call delta-Connected Components. Our general framework is a
   single-address space, distributed memory programming model. We use
   efficient techniques for distributing and coalescing data as well as
   efficient combinations of task and data parallelism. The image
   segmentation algorithm makes use of an efficient connected components
   algorithm which uses a novel approach for parallel merging. The
   algorithms have been coded in Split-C and run on a variety of
   platforms, including the Thinking Machines CM-5, IBM SP-1 and SP-2,
   Cray Research T3D, Meiko Scientific CS-2, Intel Paragon, and
   workstation clusters. Our experimental results are consistent with the
   theoretical analysis (and provide the best known execution times for
   segmentation, even when compared with machine-specific
   implementations.) Our test data include difficult images from the
   Landsat Thematic Mapper (TM) satellite data. More efficient
   implementations of Split-C will likely result in even faster execution
   times.

---
David A. Bader
Electrical Engineering Department
A.V. Williams Building
University of Maryland
College Park, MD 20742
Office: 301-405-6755  
FAX:    301-314-9658


WWW:      http://www.umiacs.umd.edu/~dbader

 
 
 

1. Fast Image Segmentation

Hello everybody,

Does anyone know if the following decision problem has an efficient
solving algorithm ?

Instance : An Image I described over grey-levels, two positive
Integers K,K'.

Question : Does there exists a partition of I into K connex regions $R_1,
..., R_K$ such that the between-regions error E of this partition
exceeds K' ?

Here, $E=\sum_{j=1}^{K} {|R_j|(\overline{R_j}-\overline{I})^2}$,
where $|R_j|$ is the cardinality (pixel number) of $R_j$,
$\overline{R_j}$ is the average grey-level of $R_j$, and
$\overline{I}$ is the average grey-level of $I$.

Should anyone know efficient algorithm for this problem (or the
optimization version, where the objective is find a valid partition
maximizing E, i.e. we remove K' from the instance), please give also
references I could use (even techreports).

Thanks a lot,

- Richard.

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