Bibtex entry:

@article{pr:Kov95a,
   keywords = {ocr, pattern recognition, nearest neighbors, algorithms},
   author = {Zs. M. Kovacs and R. Guerrieri},
   title="Massively-Parallel Hand-Written Character Recognition Based
          on the Distance Transform",
   key={pr:Kov95a},
   journal= {Pattern Recognition},
   volume = {28},
   number = {3},
   pages = {293--301},
   month = {Mar},
   year = {1995},
   abstract={
A new statistical classifier for hand-written character recognition is
presented. After a standard preprocessing phase for image binarization
and normalization, a distance transform is applied to the normalized
image, converting a black and white (B/W) into a gray scale
picture. The latter is used as feature space for a k-Nearest-Neighbor
classifier, based on a dissimilarity measure which generalizes the use
of the distance transform itself. The classifier has been implemented
on a massively-parallel processor, Connection Machine
CM-2. Classification results of digits extracted from the U.S. Post
Office ZIP code database and the upper-case letters of the NIST Test
Data 1 are provided. The system has an accuracy of 96.73% on the
digits and 94.51% on the upper-case letters when no rejection is
allowed and an accuracy of 98.96% on the digits and 98.72% on the
upper-case letters at 1% error rate.
},
}

Microelectronics Group Home Page	Staff
Research Activities	Teaching Activity
Publications	Local Stuff
DEIS Home Page	University of Bologna Home Page