The behavior of information in a process of recognition is of much theoretical interest. In order to shed some light on this behavior a case study is presented. The process chosen was that of the recognition of several computer printed characters on a noisy page. The design of the experiment was made such that the amount of missing information in the data was exactly calculable. The recognition process is iterative and is found to always terminate. Another result is that information is gained, on the average, during the process of recognition. This was true for all different characters that participated in the analysis. A connection with the theory of fuzzy pattern recognition is very clear and is discussed in detail. A correlation was found to exist between either the final average entropy per symbol, or the drop in entropy during the iterative process, and the percentage of successful detection of the same specific symbol. This fact further connects missing information with the process of learning and recognizing fuzzy data.
|Number of pages||13|
|Journal||Fuzzy Sets and Systems|
|State||Published - 20 Jul 1989|
- Pattern recognition
- fuzzy data
ASJC Scopus subject areas
- Artificial Intelligence