Accession Number : ADA307591

Title :   Machine Vision Through Machine Learning.

Descriptive Note : Final technical rept. 30 Sep 92-15 Sep 95,

Corporate Author : GEORGE MASON UNIV FAIRFAX VA

Personal Author(s) : Michalski, Ryszard

PDF Url : ADA307591

Report Date : 15 SEP 1995

Pagination or Media Count : 30

Abstract : This research has been concerned with the development of initial methodologies and vision systems capable of learning descriptions of visual objects or scenes, and the application of the learned descriptions to the efficient recognition of objects in a scene. The underlying motivation for this project is that learning capabilities will make computer vision systems adaptable to a wider range of practical problems than current vision systems that in most cases lack leaning capabilities. In this project, we concentrated on the following topics: (1) Development of the MLT ('multilevel logical templates') methodology for learning image transformations that characterize classes of visual objects. (2) Implementation of the MLT methodology and its application to the acquisition of texture descriptions by learning them from object samples presented in a scene under varied perceptual conditions and noise. (3) Development of methods that use a simple form of analogy for learning visual concepts (the PRAX project). (5) Application of the developed methods and systems to selected practical problems in the area natural object recognition, object detection in a scene, and target recognition.

Descriptors :   *IMAGE PROCESSING, *LEARNING MACHINES, *COMPUTER VISION, ALGORITHMS, NEURAL NETS, OPTIMIZATION, SYSTEMS ENGINEERING, DATA MANAGEMENT, INFRARED SIGNATURES, TARGET ACQUISITION, TARGET RECOGNITION, RESOLUTION, EFFICIENCY, INPUT OUTPUT PROCESSING, RULE BASED SYSTEMS, TARGET DISCRIMINATION, SYNTHETIC APERTURE RADAR, RADAR IMAGES, INFRARED IMAGES, DATA ACQUISITION, PATTERN RECOGNITION, KNOWLEDGE BASED SYSTEMS, RESEARCH MANAGEMENT, RADAR SIGNATURES, VISUAL TARGETS, IMAGE REGISTRATION, OBJECT ORIENTED PROGRAMMING.

Subject Categories : Cybernetics

Distribution Statement : APPROVED FOR PUBLIC RELEASE