Pattern recognition
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Pattern Recognition. Pattern - complex composition of sensory stimuli that the human observer may recognize as being a member of a class of objects Issue - what cognitive mechanisms need to be inferred to describe this process of recognition?. Bridge with Signal Detection.

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Pattern Recognition

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Pattern Recognition

Pattern - complex composition of sensory stimuli that the human observer may recognize as being a member of a class of objects

Issue - what cognitive mechanisms need to be inferred to describe this process of recognition?

Bridge with Signal Detection

  • Detection of sensory stimuli - data driven

  • Perception of Patterns - conceptually driven

  • work from the bottom (identifying stuff in the world) to the top (thinking)

Necessary Terms and Concepts of Pattern Recognition

  • Serial and Parallel Processing

    • Serial or sequential processing means we process information one step at a time, where one process must be finished before the next can be started.

    • Parallel processing means we can process several tasks at one time

Necessary Terms and Concepts of Pattern Recognition

  • Bottom-up and Top-down processing

    • Bottom-up processing is similar to inductive reasoning. Basic data are combined into more complex forms.

    • Top-down processing is similar to deductive reasoning. Higher levels of processing affect lower level tasks.

      • The following gives examples of how we perceive visual patterns and how positioning or additional information affects our perception.

Theories of Perception

1. Gestalt

(Canonic Processing)2. Bottom-Up vs. Top Down

3. Template matching

4. Feature Analysis

Prototype Theory

Form Perception

Gestalt Theory

  • Gestalt theorists are among the earliest to look at the problem of pattern recognition.

  • They postulate that we perceive stimuli as a whole pattern. That is, that individual parts have no meaning independent of the whole but combine to revel an identifiable pattern.

  • Gestalt theorists developed 5 rules of perception to explain their ideas...

Gestalt Laws

1. Law of Proximity:

  • Elements that are closer together will be perceived as a coherent object.

  • On the top, there appears to be three horizontal rows, while on the bottom, the grouping appears to be columns

Gestalt Laws

  • Law of Similarity:

    • Elements that look similar will be perceived as part of the same form.

    • There seems to be a triangle in the square.

Gestalt Laws

  • Law of Closure:

    • Humans tend to enclose a space by completing a contour and ignoring gaps in the figure

Gestalt Laws

  • Law of Prananz:

    • A stimulus will be organized into as good a figure as possible (symmetrical, simple, and regular)

    • The figure appears to the eye as a square overlapping triangle, not a combination of several complicated shapes.

Summary of Gestalt

  • Modern conclusion is that some level of “natural organization” of patterns is tied to the perceptual history of the subject

    • a function of the perceiver rather than the stimulus

Canonic Processing

  • Extension of Gestalt

  • the first images of an object that comes to mind when thinking of that particular form.

  • perspectives fluctuate with culture and time.

    • person from Los Angeles asked to think of a house might recall a one story, 3 bedroom stucco structure; a person living in a poverty-stricken Third world country might imagine a small hut made of tree branches held together with mud

Canonic Processing

  • Through common experience with objects, we develop memories of the most representational view (and gives most amount of info)

  • Studying this helps to understand form perception, prototype formation, economy of thinking, “visual shorthand”

Top-down vs. bottom up processing

  • Bottom-up processing consists of mental operations influenced by the physical properties of the stimulus.

  • Top-down processing consists of mental operations influenced by the results of processes already completed.

  • Reading the following requires both kinds of processing:


  • Problem - perception requires that information in the environment must be matched to internal information about the environment; however, the environmental information is subject to substantial variation. How do we recognize things in the face of this variability?

Template Matching

  • Template - internal constrict that, when matched by sensory stimuli, leads to the recognition of an object

  • Assumption: a retinal image of an object is faithfully transmitted to the brain and that an attempt is made to compare it directly to various stored patterns

  • details are vague

Template Matching

  • compare stimulus to large number of literal copies (templates) that are stored in memory to find match against all templates

    • works well with computers (check-sorting machines)

    • does not work well with humans -- too inflexible

      • does not account for similarities among objects

      • what is the effect of context?

Prototype Model

  • more flexible version of template model - the match does not have to be exact

    • match against “prototypical A”

  • advantages

    • manageable number of representations in memory can account for how people classify similar objects into a common category

  • disadvantages

    • lack of explicit information about how stimuli are compared to prototypes

Feature Analysis Model

  • Assumption: stimuli consist of combinations of elementary features; (e.g for the alphabet, features may include horizontal lines, vertical lines, diagonals, and curves)

    • make discriminations based on a small number of characteristics of stimuli

    • distinctive feature components stored in memory [a mini-template model??]

Feature Analysis Model

  • What is a feature?

    • A feature is a distinctive attribute or characteristic of a stimulus.

      e.g., 'T' has 2 features: ' - ' & '|'

      (E. Gibson, 1969)

Feature Analysis Model

  • Psychological Evidence: Gibson (1969)

  • decide whether or not two letters are different

    • takes longer to respond to P & R versus G & M

  • P & R share many critical features

Feature Analysis Model

  • Neurological Evidence: Hubel & Wiesel (1962)

    • microelectrodes in cats’ brains (visual cortex)

    • some neurons respond only to horizontal lines, others to diagonals...

    • similar evidence in monkeys (Maunsell & Newsome, 1987)

  • certain feature detectors are “wired” and help us identify features and simple patterns

Neisser example

  • - Look for the “X”

    O O P O P O P O P

    P O P P O P P P O

    O O P P O X P O P

    O O P O P O P O P

    P O P P O P P P O

Neisser example

  • Look for the “X”

    N N Z N Z N Z N Z

    Z N Z Z N Z Z N N

    N N N Z N X N Z N

    N N Z N Z N Z N Z

    Z N Z Z N Z Z N N

Feature Analysis

  • advantages

    • economical to store features in memory

    • experimental evidence consistent with features

  • disadvantages

    • lack of applicability to a wide range of stimuli

    • analysis of stimuli does not always begin with features

    • treats all features as equivalent

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