The book begins by introducing the concept of inductive learning and provides an exhaustive coverage of the procedures for Pattern Recognition. Pattern Recognition: Techniques and Applications would serve as a textbook for undergraduate and master's Engineering students for the course on Pattern Recognition. It would also be a useful reference for practicing engineers in industrial and research organizations that apply pattern recognition techniques in diverse areas such as optical character recognition, speech recognition, etc. The book begins by introducing the concept of inductive learning and provides an exhaustive coverage of the procedures for Pattern Recognition. Other relevant topics such as feature selection and clustering are also dealt with. The last chapter compares the results of classifying a given problem by each procedure, and proposes research on finding their underlying commonality, if any. The book is well supported by both programming and non-programming exercises at the end of each chapter. The appendices describe syntactic pattern recognition as well as two projects for students: one on medical prognostication and the other on optical character recognition. The lucid treatment in the book encourages self-study and instills working knowledge of pattern recognition in a student.