  This paper addresses the automatic recognition of handwritten temperature
values in weather records. The localization of table cells is based on line
detection using projection profiles. Further, a stroke-preserving line removal
method which is based on gradient images is proposed. The presented digit
recognition utilizes features which are extracted using a set of filters and a
Support Vector Machine classifier. It was evaluated on the MNIST and the USPS
dataset and our own database with about 17,000 RGB digit images. An accuracy of
99.36% per digit is achieved for the entire system using a set of 84 weather
records.
