Robert Haralick was born in Brooklyn, New York, on September 30, 1943. He
received a B.A. degree in Mathematics from the University of Kansas in 1964,
a B.S. degree in Electrical Engineering in 1966 and a M.S. degree in Electrical
Engineering in 1967.
In 1969, after completing his Ph.D. at the University of Kansas, he joined the
faculty of the Electrical Engineering Department there where he last served as
Professor from 1975 to 1978. In 1979 Dr. Haralick joined the Electrical
Engineering Department at Virginia Polytechnic Institute and State University
where he was a Professor and Director of the Spatial Data Analysis Laboratory.
From 1984 to 1986 Dr. Haralick served as Vice President of Research at Machine
Vision International, Ann Arbor, MI. Dr. Haralick occupied the Boeing
Clairmont Egtvedt Professorship in the Department of Electrical Engineering
at the University of Washington from 1986 through 2000. At UW Dr. Haralick was an
adjunct professor in the Computer Science Department and the Bioengineering Department.
In 2000 Dr. Haralick
accepted a Distinguished Professorship position at the Computer Science Department,
Graduate Center, City University of New York.
Professor Haralick has
made a series of contributions in computer vision.
In the high--level vision area, he has worked
on inferring 3D geometry from one or more perspective projection
views. He has also
identified a variety of vision problems which are special cases of the
consistent labeling problem.
His papers on consistent labeling, arrangements,
relation homomorphism, matching,
and tree search translate
some specific computer vision problems to the more general combinatorial
consistent labeling problem and then discuss the theory of the look--ahead
operators that speed up the tree search. This gives a framework for the
control structure required in high--level vision problems.
He has also extended the forward--checking
tree search technique to propositional
In the low--level and mid--level areas, Professor Haralick
in image texture analysis using spatial
gray tone co--occurrence texture features.
These features have been used with success on biological cell images,
x--ray images, satellite images, aerial images and many other kinds of images taken
at small and large scales.
In the feature detection area, Professor Haralick has developed the facet
model for image processing. The facet model states that many low--level
image processing operations can be interpreted relative to what the
processing does to the estimated underlying gray tone intensity surface
of which the given image is a sampled noisy version.
facet papers develop techniques for
edge detection, line detection, noise removal, peak and pit detection, as
well as a variety of other topographic gray tone surface features.
Professor Haralick's work in shape analysis and extraction uses the
techniques of mathematical morphology.
He has developed the
morphological sampling theorem which
establishes a sound shape/size basis for the focus of
attention mechanisms which can process image data in a
multiresolution mode, thereby
making some of the image feature extraction processes execute more efficiently.He has also developed recursive morphological algorithms for the
computation of opening and closing transforms. The recursive algorithms
permit all possible sized openings or closings for a given structuring
element to be computed in constant time per pixel.
In the area of document image understanding, Professor Haralick
is responsible for the development of comprehensive ground-truthed
data bases consisting of over 1500 document images most in English
and some in Japanese. The data bases are issued in CDROMs and are being used
all around the world by people who are developing character recognition
methodologies and techniques for document image structural
decomposition. He has developed algorithms for document image
skew angle estimation, zone delineation, word and text line bounding
In a series of papers, Professor Haralick has helped influence
the computer vision community to be more sensitive to the needs of computer
vision performance characterization and covariance propagation. His most
recent work is in the pattern recognition area, particularly
in the manifold clustering of high dimensional data sets, the application of
pattern recognition to mathematical combinatorial problems and in is the area of [[Torah codes]] popularly called [[bible code]]s. In this area he has co-authored a book with Professor Eliyahu Rips, one of the coauthors of the original ''Statistical Sciences'' paper. Dr. Haralick's research has helped develop
sophisticated algorithmic and statistical methodology for Torah code experiments,
methodology that can differentiate between the tables that are deceptively depicted
as encodings in books like ''Moby Dick'' and ''War and Peace'' from those real
encodings that occur in the Torah text.
Professor Haralick is a Fellow of IEEE for his contributions in
computer vision and image processing and a Fellow of the International Association
for Pattern Recognition (IAPR) for his
contributions in pattern recognition, image processing, and for service
to IAPR. He served as president of IAP in 1996-1998. He has
served on the Editorial Board of
''IEEE Transactions on Pattern Analysis and Machine Intelligence'' and has been
the computer vision area
editor for ''Communications of the ACM'' and as an associate
editor for ''Computer Vision, Graphics, and Image Processing'',
''The IEEE Transactions on Image Processing'' and
''Pattern Recognition''. He served on the
editorial board of ''Real Time Imaging'' and the editorial board
of ''Electronic Imaging''. His publications include over 550 archival papers,
book chapters, conference proceedings and books.
Professor Haralick has been recognized for his academic research in the Marquis Who's Who books.
He is listed in the current editions for Who's Who in the East,
Who's Who in America, and Who's Who in the World.