Preface

The impact of pattern recognition on the improvement of human life cannot go unnoticed. Additionally, its uni ue ualities have aroused considerable interest and are desired by the military, many governmental institutions and state offices, as well as ordinary people.

Significantly, systems of pattern recognition are becoming increasingly applicable in many areas with various studies on new methods and prototypes being carried out in different countries now reaching thousands. Pattern recognition combined with biometrics creates security systems that protect objects from unauthorized persons on the one hand andsystems that support the protection of significant state infrastructure facilities such as airports, ports, and many more on the other. In medicine, pattern recognition helps diagnosticians and doctors to detect abnormal lesions and disease outbreaks, and create systems for early diagnosis of diseases. Technical sciences among others use pattern recognition in the identification of prefailure states. One could point to hundreds of other applications. The wide application of pattern recognition in many areas of human activity is now more than obvious. Unlocking our smartphone with a fingerprint or showing our face would not be possible without pattern recognition methods. This has resulted in the design of novel methods, algorithms, and systems that are directly or indirectly connected with pattern recognition.

I hope that this book will contribute to the propagation and further development of knowledge in the field of pattern recognition.

> **Andrzej Zak** Polish Naval Academy, Gdynia, Poland

**1**

**Chapter 1**

*Andrzej Zak*

**1. Introduction**

Introductory Chapter: Pattern

Recognition as Cognitive Process

The development of science and rapid advances in technology have created many new problems that mankind is currently encountering. The solution to the majority of these problems is based on information processing. We can easily say that without information processing, our civilization, in the form we know, could not exist, and information is a key element of the decision-making process. Decision-making is inextricably linked to the automation of various processes. Currently, the trend is automated by performing operations with the characteristics of intelligence, which until now were performed only by people. An example here can be systems that have speech recognition capabilities, images recognition (reading hand-writing letters and signature recognition), people recognition (biometric systems), text translations, chess games, proofs of claims, and many others. The

The concept of pattern recognition is difficult to define unequivocally. The laconic definition will be too short to reflect the nature and essence of the concept. In turn, a too long definition causes the blurring of the essence of the problem. Pattern recognition is a scientific issue that has its roots among others in information theory, mathematical analysis and statistics, signal and image processing, machine learning, artificial intelligence, and many others. The possibilities of implementing algorithms from this area as well as the application potential of the developed solutions mean that this field of knowledge is most often identified with automation and robotics, mechatronics, and computer science. The methods, algorithms, and tools used in other scientific areas, e.g., artificial neural networks, optimization methods, genetic and evolutionary algorithms, fuzzy logic, etc., are often used to create and implement practical solutions in the field of pattern recognition. The pattern recognition process itself can be treated as an action consisting in retrieving raw data and taking further actions depending on the category to which these data belong. It is most commonly assumed that the main areas of application of pattern recognition in the field of technical sciences are signal and image analysis systems. However, it should be noted that pattern recognition can be successfully used in medical sciences, e.g., in the identification of diseases or in social sciences, e.g.,

basis for solving these tasks is methods for pattern recognition.

when recognizing the behavior of each individual or a group.

Recognition of patterns aims at classifying objects based on statistical data collected for the purpose of extracting features of objects based on a priori information or using self-learning. Classified objects are usually groups of measurement or observation results defining the location of corresponding points in the multidimensional space of features. In other words, pattern recognition is a procedure in which individual items are placed into groups based on quantitative information on one or more characteristics inherent in the items (referred to as traits, variables,

characters, etc.) and based on a training set of previously labeled items.
