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This article is about pattern recognition in physiological systems. For the application of the term in machine learning see: Pattern recognition
Pattern recognition involves identification of faces, objects, words, melodies, etc. The visual system does more than just interpret forms, contours and colors. Pattern recognition refers to the process of recognizing a set of stimuli arranged in a certain pattern that is characteristic of that set of stimuli. Pattern recognition is an innate ability of animals.
Theories of pattern recognitionEdit
- Template matching theory of pattern recognition
- Prototype matching theory of pattern recognition
- Feature analysis theory of pattern recognition
- Recognition by components theory of pattern recognition
- Fourier analysis
- Bottom-up and top-down processing
Template matching theoryEdit
The incoming sensory information is compared directly to copies (templates) stored in the long term memory. These copies are stored in the process of our past experiences and learning.
Eg. A A A are all recognized as the letter A
Prototype matching theoryEdit
Prototype means a concept of average characteristics of a particular subject. For instance a concept of small animal with feathers, beak, two wings that can fly is a prototype concept of a crow, sparrow, hen, eagle, etc. Prototype matching unlike template matching does not emphasize a perfect match between the incoming stimuli and the stored concept in the brain.
Feature analysis theoryEdit
According this theory, the visual system breaks down the incoming stimuli into its features and process the information. Some features may be more important for recognition than others. All stimuli have a set of distinctive features. Feature analysis proceeds through 4 stages.
- Pattern dissection
- Feature comparison in memory
Theory of recognition of components (Irving Biederman)Edit
According this theory every object is made up of Geons - the building blocks of all objects (cylinders, cones, are combined in many ways (on top of, to the side, etc.).
Hierarchy of detectors:
- feature detectors - lowest; respond to curves, edges, etc.
- geon detectors - activated by feature detectors
- higher level detectors - recognize combinations of features and geons
According Biederman an individual on an average is familiar with about 30,000 objects and recognizing them requires no more than 36 geons. Well this was a fun thing to be good at being good at. because it helps with your science h/w!!!
References & BibliographyEdit