Human decision making procedures in problems related with analysis of time series data bases (TSDB) often use perceptions like “several days”, “high price”, “quickly increasing” etc. Computing with Words and Perceptions can be used to formalize perception based expert knowledge and inference mechanisms defined on numerical domains of TSDB. For extraction from TSDB perception based information relevant to decision making problems it is necessary to develop methods of perception based time series data mining (PTSDM). The paper considers different approaches used in analysis of time series databases for description of perception based patterns and discusses some methods of PTSDM.