Syntactic pattern recognition, or structural pattern recognition, is a form of

pattern recognition Pattern recognition is the task of assigning a class to an observation based on patterns extracted from data. While similar, pattern recognition (PR) is not to be confused with pattern machines (PM) which may possess PR capabilities but their p ...

in which each object can be represented by a variable-

cardinality The thumb is the first digit of the hand, next to the index finger. When a person is standing in the medical anatomical position (where the palm is facing to the front), the thumb is the outermost digit. The Medical Latin English noun for thum ...

set of symbolic nominal features. This allows for representing pattern structures, taking into account more complex relationships between attributes than is possible in the case of flat, numerical feature vectors of fixed dimensionality that are used in

statistical classification When classification is performed by a computer, statistical methods are normally used to develop the algorithm. Often, the individual observations are analyzed into a set of quantifiable properties, known variously as explanatory variables or ''f ...

. Syntactic pattern recognition can be used instead of statistical pattern recognition if clear structure exists in the patterns. One way to present such structure is via strings of symbols from a

formal language In logic, mathematics, computer science, and linguistics, a formal language is a set of strings whose symbols are taken from a set called "alphabet". The alphabet of a formal language consists of symbols that concatenate into strings (also c ...

. In this case, the differences in the structures of the classes are encoded as different grammars. An example of this would be diagnosing

heart The heart is a muscular Organ (biology), organ found in humans and other animals. This organ pumps blood through the blood vessels. The heart and blood vessels together make the circulatory system. The pumped blood carries oxygen and nutrie ...

problems with electrocardiogram (ECG) measurements. ECG

waveform In electronics, acoustics, and related fields, the waveform of a signal is the shape of its Graph of a function, graph as a function of time, independent of its time and Magnitude (mathematics), magnitude Scale (ratio), scales and of any dis ...

s can be approximated with diagonal and vertical line segments. If normal and unhealthy waveforms can be described as formal grammars, ECG signals can be classified as healthy or unhealthy by first describing them in terms of the basic line segments, and then trying to parse the descriptions according to the grammars. Another example is tessellation of tiling patterns. A second way to represent relations are graphs, where nodes are linked if corresponding subpatterns are related. An item can be assigned a certain class label if its graph representation is

isomorphic In mathematics, an isomorphism is a structure-preserving mapping or morphism between two structures of the same type that can be reversed by an inverse mapping. Two mathematical structures are isomorphic if an isomorphism exists between the ...

with prototype graphs of that class. Typically, patterns are constructed from simpler sub-patterns in a hierarchical fashion. This helps divide the recognition task into easier subtasks of first identifying sub-patterns, and then the actual patterns. Structural methods provide descriptions of items, which may be useful in their own right. For example, syntactic pattern recognition can be used to determine what objects are present in an image. Furthermore, structural methods are strong when applied to finding a "correspondence mapping" between two images of an object. Under natural conditions, corresponding features will be in different positions and/or may be occluded in the two images, due to camera attitude and perspective, as in face recognition. A graph matching algorithm will yield the optimal correspondence.

References

{{cite book , last= Flasinski, first = Mariusz , title = Syntactic pattern recognition , publisher = World Scientific , year = 2019 , ISBN = 978-981-3278-46-2 Classification algorithms

See also

References