@article{1915,
  author = {Ali Samei, Alireza Tvakoli Talrghi, Mohammad Mahdi Dehshibi},
  title = {MedLab: Medical Labratoary Test Document Analysis Using HoG and SVM},
  journal = {Progress in Computing Applications},
  year = {2015},
  volume = {4},
  number = {2},
  doi = {},
  url = {http://www.dline.info/pca/fulltext/v4n2/v4n2_3.pdf},
  abstract = {This paper presents an automatic document processing system for the extraction of data which are illustrated
in medical laboratory results printed on a paper. The final goal of the research is to make the collection of medical data
automatic and to enable an efficient management and description of the information in a way that a patient or a senior
medicine student can understand the document just like an expert physician. In order to reach the mentioned goals, following
the forthcoming steps was necessary in the proposed method. (i) Image pre-preprocessing, (ii) layout analysis for the
identification of the tables’ data contained in the document’ (iii) extraction and classification of the laboratory results using
template matching and HoG features in combination with a Support Vector Machine (SVM). Providing information for the
application user need to constructing a knowledge base in which the relevant information of Wikipedia is used. The proposed
approach has been tested on several document formats and performance analysis shows its superiority as well as simplicity.},
}