Pattern Recognition, What does Pattern Recognition mean?

Pattern recognition is a basic human intelligence, in daily life, people often in the "pattern recognition". With the emergence of computers in the 1940s and the rise of artificial intelligence in the 1950s, people certainly hope to use computers to replace or extend some of the human brain work. Pattern recognition (computerized) developed rapidly in the early 1960s and became a new discipline. What are patterns and pattern recognition? Broadly speaking, the existence of observable things in time and space, if you can distinguish whether they are the same or similar, can be called patterns; narrowly speaking, the pattern is through the observation of specific individual things with a temporal and spatial distribution of information; the pattern belongs to the category or the pattern of the same class of the overall pattern is called the pattern of classes (or simply for the class). The "pattern recognition" is in some certain measure or observation based on the pattern to be recognized into the respective pattern class. The study of pattern recognition focuses on two aspects, namely, the study of how living organisms (including human beings) perceive objects, and the theory and method of how to realize pattern recognition by computer under a given task. The former is the research of physiologists, psychologists, biologists, neurophysiologists and belongs to the category of cognitive science; the latter has achieved systematic research results through the efforts of mathematicians, informatics experts and computer scientists in recent decades. A computer pattern recognition system is basically composed of three interrelated but distinctly different processes, i.e., data generation, pattern analysis and pattern classification. Data generation is to convert the raw information of the input patterns into vectors into a form that can be easily processed by the computer. Pattern analysis is the processing of the data, including feature selection, feature extraction, data dimensionality compression, and determination of possible categories. Pattern classification, on the other hand, uses the information obtained from pattern analysis to train the computer to develop discriminatory criteria with a view to classifying the patterns to be recognized. There are two basic types of pattern recognition methods, namely, statistical pattern recognition methods and structural (syntactic) pattern recognition methods. Statistical pattern recognition is a statistical classification method for patterns, i.e., a technique for pattern recognition that incorporates the Bayesian decision system of statistical probability theory, also known as decision-theoretic recognition methods. The pattern recognition work done by using the tree information of the hierarchical structure of patterns and sub-patterns is structural pattern recognition or syntactic pattern recognition. Applications of pattern recognition include text recognition, speech recognition, fingerprint recognition and so on. Pattern recognition technology is the basic technology of artificial intelligence, the 21st century is the century of intelligence, informatization, computation and networking, in this century characterized by digital computing, pattern recognition technology, as the basic discipline of artificial intelligence technology, is bound to gain huge development space. Internationally, major authoritative research institutions, major companies have begun to pattern recognition technology as the company's strategic research and development focus on attention. Pattern recognition (Pattern Recognition) refers to the characterization of things or phenomena of various forms of (numerical, textual and logical relationships) information processing and analysis, in order to describe things or phenomena, identification, classification and interpretation process, is an important part of information science and artificial intelligence. Schema can also be divided into abstract and concrete forms. The former, such as consciousness, thoughts, arguments, etc., belongs to the scope of concept recognition research, which is another research branch of artificial intelligence. What we mean by pattern recognition is mainly to classify and recognize the concrete patterns of measurement of objects such as speech waveforms, seismic waves, electrocardiograms, electroencephalograms, pictures, photographs, words, symbols, sensors of living beings, etc. A computer is applied to identify and categorize a set of events or processes. The events or processes identified can be concrete objects such as words, sounds, images, etc., or abstract objects such as states and degrees. These objects are distinguished from information in digital form and are called pattern information. Pattern recognition is related to statistics, psychology, linguistics, computer science, biology, cybernetics and so on. It is interrelated with the study of artificial intelligence and image processing. For example, adaptive or self-organizing pattern recognition system contains the learning mechanism of artificial intelligence; artificial intelligence research landscape understanding, natural language understanding also contains pattern recognition issues. Another example is that the preprocessing and feature extraction in pattern recognition applies the technology of image processing; the image analysis in image processing also applies the technology of pattern recognition. Pattern recognition research is mainly focused on two aspects, one is the study of organisms (including people) is how to perceive the object, belongs to the category of cognitive science, the second is in the given task, how to use the computer to realize the theory and method of pattern recognition. The former is physiologists, psychologists, biologists and neurophysiologists of the research content, the latter through the mathematicians, informatics experts and computer scientists in recent decades, has achieved systematic research results. "Pattern Recognition" is a technology that uses machines to simulate human recognition of things. It is a branch of information science, is an important part of the discipline of artificial intelligence. Earlier pattern recognition is mainly from the mathematical theory to study and distinguish the characteristics of things. After the invention of electronic computers, the realization of the machine instead of human identification work. Electronic computers are the ideal equipment for pattern recognition instead of people, therefore, the current pattern recognition technology is mainly the use of electronic computer technology to realize the mathematical theory of analysis and calculation. Pattern recognition is a general discipline. In telecommunication, it is used in voice-controlled telephone dialing, automatic response to user inquiries, and automatic voice recognition of designated speakers. In addition, it is also widely used in medical, national defense, public security and other sectors. For example, iris recognition system, fingerprint automatic identification system, voice recognition machine, text reader, etc. used for identity recognition are already mature products. Intelligent computers and intelligent robots will also reach a higher level with the development of pattern recognition technology. Pattern recognition can also be used for text and speech recognition, remote sensing and medical diagnosis. ① Text recognition Chinese characters have a history of thousands of years, but also the world's largest number of people use the text, for the formation and development of the Chinese nation's splendid culture has indelible merit. Therefore, today, when information technology and computer technology are becoming more and more popular, how to input characters into computer conveniently and quickly has become an important bottleneck affecting the efficiency of human-computer interface, and it is also related to whether computers can be really popularized and applied in our country. At present, Chinese character input is mainly divided into two kinds: manual keyboard input and automatic machine recognition input. Among them, manual input is slow and labor-intensive; automatic input is divided into Chinese character recognition input and voice recognition input. In terms of the difficulty of recognition technology, the difficulty of handwriting recognition is higher than that of print recognition, and in handwriting recognition, the difficulty of offline handwriting is much higher than that of on-line handwriting recognition. So far, in addition to the recognition of offline handwriting numbers have practical applications, Chinese characters and other text offline handwriting recognition is still in the laboratory stage. ② Speech recognition speech recognition technology technology involved in the field of signal processing, pattern recognition, probability theory and information theory, vocal mechanism and auditory mechanism, artificial intelligence and so on. In recent years, in the field of biometrics technology, voice recognition technology has been noticed by the world for its unique convenience, economy and accuracy, and has increasingly become an important and popular security verification method in people's daily life and work. And the speech recognition method using genetic algorithm to train continuous hidden Markov model has now become the mainstream technology of speech recognition, which has faster recognition speed and higher recognition rate in speech recognition. 2.3 Fingerprint Recognition The lines produced by the unevenness of the skin on the inner surface of our palms and their fingers, feet, and toes will form a variety of patterns. And these skin patterns vary in patterns, breaks and intersections and are unique. By relying on this uniqueness, a person can be matched to his fingerprints, and his true identity can be verified by comparing his fingerprints with pre-saved fingerprints. Generally, fingerprints are divided into the following categories: left loop, right loop, twin loop, whorl, arch and tented arch, so that each person's fingerprints can be categorized and retrieved separately. Fingerprint recognition can be basically divided into: preprocessing, feature selection and pattern classification in several major steps. Remote Sensing Remote sensing image recognition has been widely used in crop estimation, resource survey, weather forecasting and military reconnaissance. ④ Medical diagnosis Pattern recognition has been effective in cancer cell detection, X-ray photo analysis, blood tests, chromosome analysis, ECG diagnosis and EEG diagnosis.