摘要：The state of any system is defined by data of some sort. Data by itself is meaningless unless it is transformed into information by putting it into a meaningful context. Images are also defined by data accumulated by quantification of color intensities of pixels. Either the values of the pixels form patterns or the arrangement of pixels form patterns. Various statistical and probabilistic models have been employed by the researchers to extract interesting information from data. Also the pattern recognition problems are divided into two levels termed as generic and specific. In this piece of work we identify problems from both these domains of pattern recognition. This comprehensive survey not only provides a tutorial on the probabilistic and neuro-cognitive techniques used for this purpose but it also explores monumental issues in the domain.
