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Selected papers on image processing and image analysis
Updated: Aug 23, 2022
Low-level image processing
- Implementation efficiency of binary morphology
(in pdf or
gzipped ps),
D. S. Bloomberg, Mathematical Morphology and its
applications to image and signal processing: Proceedings
of the Sixth International Symposium on Mathematical
Morphology, pp. xx, CSIRO Pub, April 2002.
An informal introduction and overview of this paper
exists (in pdf or
gzipped ps).
- Pattern matching using the blur hit-miss transform
(in pdf or
gzipped ps),
D. S. Bloomberg and L. Vincent, Journal of Electronic
Imaging, Vol 9(2), pp. 140-150, April 2000.
- Connectivity-preserving morphological image
transformations
(in pdf or
gzipped ps),
D. S. Bloomberg, SPIE Conf. 1606, Visual Communications and
Image Processing '91, pp. 320-334, Boston, MA,
November 11-13, 1991.
- Generalized hit-miss operations
(in pdf or
gzipped ps),
D. S. Bloomberg and P. Maragos, SPIE Conf. 1350, Image Algebra and
Morphological Image Processing, pp. 116-128, San Diego,
CA, July 9-13, 1990. This paper is a slightly revised version,
with an added figure.
- Generalized hit-miss operators with applications to
document image analysis
(in pdf or
gzipped ps),
D. S. Bloomberg and P. Maragos. This is an unpublished
version of the SPIE paper above, with a significantly
expanded section on blur and rank order versions of
the hit-miss operator.
Basic methods of image segmentation
- Textured reductions for document image analysis
(in pdf or
gzipped ps),
D. S. Bloomberg, SPIE Conf. 2660, Doc. Rec. III,
pp. 160-174 , San Jose, CA, Jan. 30-31, 1996.
- Image analysis using threshold reduction
(in pdf or
gzipped ps),
D. S. Bloomberg,
SPIE Conf. 1568, Image Algebra and Morphological Image
Processing II, pp. 38-51, San Diego, CA, July 23-24, 1991.
- Multiresolution morphological
approach to document image analysis
(in pdf or
gzipped ps),
D. S. Bloomberg, International Conference
on Document Analysis and Recognition, pp. 963-971,
Saint-Malo, France, Sept. 30 - Oct 2, 1991.
Document Image Decoding
- An iterative algorithm for optimal message recognition
in linguistically constrained document image decoding
(in pdf),
K. Popat, D. S. Bloomberg and D. Greene,
Proceedings of the 4th IAPR Workshop on Document
Analysis Systems, Springer, 2002.
- Document image decoding using iterated complete path
search with subsampled heuristic scoring
(in pdf or
gzipped ps),
D. S. Bloomberg, T. P. Minka and K. Popat,
Proceedings of the IAPR 2001 International Conference
Document Analysis and Recognition (ICDAR 2001), September 2001.
- Document image decoding using iterated complete path
heuristic
(in pdf or
gzipped ps),
T. Minka, D. S. Bloomberg and K. Popat,
SPIE Conf. 4307, Document Recognition and Retrieval VIII,
pp. 251--258, San Jose, CA, Jan. 24-25, 2001.
- Adding linguistic constraints to document image decoding:
comparing the iterated complete path and stack algorithms,
K. Popat, D. Greene, J. Romberg and D. S. Bloomberg,
SPIE Conf. 4307, Document Recognition and Retrieval VIII,
pp. 259--271, San Jose, CA, Jan. 24-25, 2001.
Image Compression
- Two-stage lossy/lossless compression of grayscale document
images, (in pdf),
K. Popat and D. S. Bloomberg,
Mathematical Morphology and its applications to image and
signal processing: Proceedings of the Fifth International Symposium
on Mathematical Morphology, pp. 361-370,
Kluwer Acad. Pub, June 2000.
- Google Books: Making the public domain universally
accessible (in pdf),
A. Langley and D. S. Bloomberg,
SPIE Conf. 6500, Doc. Rec. and Retrieval XIV,
paper 6500-16, San Jose, CA, Jan 30 - Feb 1, 2007.
Simple Document Image Applications
- Determining the resolution of scanned document images
(in pdf or
gzipped ps),
D. S. Bloomberg, SPIE Conf. 3651, Doc. Rec. VI,
pp. 10-21, San Jose, CA, Jan 27-28, 1999.
- Identifying document image skew and orientation
(in pdf or
gzipped ps),
D. S. Bloomberg, G. E. Kopec and L. Dasari,
SPIE Conf. 2422, Doc. Rec. II,
pp. 302-316, San Jose, CA, Feb. 6-7, 1995.
Complex Document Applications using Segmentation
- Summarization of imaged documents without OCR,
F. R. Chen and D. S. Bloomberg,
CVIU, Vol 70, No 3, pp. 307-320, 1998.
- Reading digital data embedded in iconic text,
D. S. Bloomberg, SPIE Conf. 3305, Doc. Rec. V,
pp. 194-207, San Jose, CA, Jan. 28-29, 1998.
- Extraction of indicative summary sentences from
imaged documents, F. R. Chen and D. S. Bloomberg,
ICDAR '97, pp. 227-232, Ulm, Germany, Aug. 18-20, 1997.
- Image-based document summarization,
F. R. Chen and D. S. Bloomberg, Symp. Doc. Image Under. Tech,
Annapolis, MD, Apr. 30 - May 2, 1997.
- Embedding digital data on paper in iconic text,
D. S. Bloomberg, SPIE Conf. 3027, Doc. Rec. IV,
pp. 67-80, San Jose, CA, Feb. 12-13, 1997.
- Document image summarization without OCR,
D. S. Bloomberg and F. R. Chen, Int. Conf. Image Proc. 1996,
Vol. II, pp. 229-232, Lausanne, Switzerland,
Sept. 16-19, 1996.
- Extraction of text-related features for condensing image
documents, D. S. Bloomberg and F. R. Chen,
SPIE Conf. 2660, Doc. Rec. III, pp. 72-88, San Jose,
CA, Jan. 30-31, 1996.
Papers by Luc Vincent
Luc Vincent has made available a large number of his outstanding
published
papers,
all in DjVu format. (DjVu is a "mixed raster" format, with
separate text/line-graphics and image layers, both of which are
compressed using lossy methods. The text layer is compressed
by "tokenization": the connected components are identified
and those that are nearly indistinguishable visually are
grouped together by an unsupervised classifier. Only one
of these tokens from each class is used to reproduce the image;
in the file it is compressed by an arithmetic coding scheme.
Wavelet compression is used on the image parts. The result
is the finest document image compression method -- from
a rate-distortion perspective -- available.)
Comprehensive bibliography
There is a comprehensive
bibliography of of "computer vision", image processing, and related
topics.
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