A Recognition System Using Probabilistic Decisions Based on Extracted Features

P. Murden, M. Symons
1969 International Joint Conference on Artificial Intelligence  
The paper describes a pattern recognition system that has been simulated using a computer with an on-line camera input. The system is adaptive, using a training set of pictures together with the names or classes to which each picture belongs. The system uses an edge following technique for extracting features from the multilevel inputs. During the training mode, some of the descriptors derived from the extracted features are stored. Also, the system builds up statistics of the likelihood of a
more » ... cture belonging to a given class given the presence of each incoming feature. During the test mode, a previously unseen set of pictures is used and features are extracted and compared with the stored descriptors. A sequential decision mechanism uses these comparisons and the likelihood statistics to produce responses corresponding to the assessed class of the input. Some preliminary experimental results are given.
dblp:conf/ijcai/MurdenS69 fatcat:mkaa6wxbzfdxdgq2mxzljqgzlu