Distortion-Invariant Optical Pattern Recognition by Correlative Matrix Feature Criterion,

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Abstract:

In this paper, we used correlative matrix as a feature criterion in K-L transformation for feature compression, and then the synthetic matched filter SMF was prepared by means of the synthetic discriminant function SDF. This method can effectively reduce the size of feature image. By this fiber, the shift, scale and rotation in variant optical pattern recognition was realized with a high signal noise ratio of correlation output. AN

Author(s):
Baotang, Yang ; Zhengping, Lan
Author Organization(s):
NATIONAL AIR INTELLIGENCE CENTER WRIGHT-PATTERSON AFB OH
Supplementary Note:
Trans. of Guangxue Xuebano, v12 n1 p52-56 Jan 92.
Annotation:
Distortion-Invariant Optical Pattern Recognition by Correlative Matrix Feature Criterion. --Translation.
Pagination:
0012

Security Markings

DOCUMENT & CONTEXTUAL SUMMARY

Distribution:
Approved For Public Release

RECORD

Collection: TR
Identifying Numbers
Report Number(s):
NAIC-ID(RS)T-0387-94
Monitor Series:
NAIC*
 Subject Terms
Joint Capability Areas:
JCA_1.2_Force Preparation; JCA_1_Force Support; JCA_6.3.3_Spectrum Management; JCA_6_Net Centric
Modernization Areas:
AI and Machine Learning
Communities of Interest:
Air Platforms
Descriptor(s):
*IMAGE PROCESSING, *PATTERN RECOGNITION, ALGORITHMS, COMPUTERIZED SIMULATION, MATRICES(MATHEMATICS), SIGNAL TO NOISE RATIO, OPTICAL IMAGES, VARIATIONS, TRANSFORMATIONS(MATHEMATICS), CORRELATION, OPTICAL ANALYSIS, COMPUTER GRAPHICS, TRANSLATIONS, DATA COMPRESSION, MATCHED FILTERS, DISTORTION, CHINA, DISCRIMINATE ANALYSIS, INFORMATION PROCESSING, CHINESE LANGUAGE, HOLOGRAMS
Field(s)/Group(s):
Cybernetics, Computer Programming and Software, Optics
Keyword(s):
FOREIGN REPORTS
Report Date:
1994 Dec 29