Performance of a Working Face Recognition Machine using Cortical Thought Theory

Abstract

A face recognition system was developed, based on the principles of Cortical Thought Theory (CTT), recently proposed by Dr. Richard L. Routh as his doctoral dissertation at the Air Force Institute of Technology. Routh tested the CTT architecture successfully for speech processing. In order to evaluate this architecture as a generic sensory information processing model, CTT was tested for visual processing, specifically for the difficult task of human face recognition. The CTT gestalt transformation maps a 2-dimensional images into a 2-D coordinate point. The present system extracts six sub-images from a contrast-expanded image, calculates the 2-D gestalt coordinates, and stores the information in a database. Statistics are then calculated on at least five prototypes processed for each person. Overall performance of different sub- windows on a face are also determined. An unidentified person is recognized by calculating the six gestalt feature vectors, and then finding the closest match to previously stored data. The computer generates an order list by closeness of match. Performance testing of the system yielded a reliability of 90%.

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Document Details

Document Type
Technical Report
Publication Date
Dec 04, 1984
Accession Number
ADA167781

Entities

People

  • Robert L. Russel Jr.

Organizations

  • Air Force Institute of Technology

Tags

Communities of Interest

  • Energy and Power Technologies
  • Human Systems
  • Space

DTIC Thesaurus Topics

  • Accuracy
  • Air Force
  • Artificial Intelligence
  • Automata
  • Automated Speech Recognition
  • Computer Architecture
  • Computer Vision
  • Computers
  • Data Processing
  • Databases
  • Electrical Engineering
  • Image Processing
  • Image Recognition
  • Information Processing
  • Pattern Recognition
  • Performance Tests
  • Two Dimensional

Readers

  • Artificial Intelligence
  • Neural Network Machine Learning.
  • Psychometric Testing or Psychological Assessment.

Technology Areas

  • AI & ML