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Title: Method for indexing and retrieving manufacturing-specific digital imagery based on image content

Abstract

A method for indexing and retrieving manufacturing-specific digital images based on image content comprises three steps. First, at least one feature vector can be extracted from a manufacturing-specific digital image stored in an image database. In particular, each extracted feature vector corresponds to a particular characteristic of the manufacturing-specific digital image, for instance, a digital image modality and overall characteristic, a substrate/background characteristic, and an anomaly/defect characteristic. Notably, the extracting step includes generating a defect mask using a detection process. Second, using an unsupervised clustering method, each extracted feature vector can be indexed in a hierarchical search tree. Third, a manufacturing-specific digital image associated with a feature vector stored in the hierarchicial search tree can be retrieved, wherein the manufacturing-specific digital image has image content comparably related to the image content of the query image. More particularly, can include two data reductions, the first performed based upon a query vector extracted from a query image. Subsequently, a user can select relevant images resulting from the first data reduction. From the selection, a prototype vector can be calculated, from which a second-level data reduction can be performed. The second-level data reduction can result in a subset of feature vectors comparable tomore » the prototype vector, and further comparable to the query vector. An additional fourth step can include managing the hierarchical search tree by substituting a vector average for several redundant feature vectors encapsulated by nodes in the hierarchical search tree.« less

Inventors:
; ;
Issue Date:
Research Org.:
Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
Sponsoring Org.:
USDOE
OSTI Identifier:
1174907
Patent Number(s):
6751343
Application Number:
09/399,394
Assignee:
UT-Battelle, LLC (Oak Ridge, TN)
Patent Classifications (CPCs):
G - PHYSICS G06 - COMPUTING G06F - ELECTRIC DIGITAL DATA PROCESSING
DOE Contract Number:  
AC05-96OR22464
Resource Type:
Patent
Country of Publication:
United States
Language:
English
Subject:
47 OTHER INSTRUMENTATION

Citation Formats

Ferrell, Regina K., Karnowski, Thomas P., and Tobin, Jr., Kenneth W. Method for indexing and retrieving manufacturing-specific digital imagery based on image content. United States: N. p., 2004. Web.
Ferrell, Regina K., Karnowski, Thomas P., & Tobin, Jr., Kenneth W. Method for indexing and retrieving manufacturing-specific digital imagery based on image content. United States.
Ferrell, Regina K., Karnowski, Thomas P., and Tobin, Jr., Kenneth W. Tue . "Method for indexing and retrieving manufacturing-specific digital imagery based on image content". United States. https://www.osti.gov/servlets/purl/1174907.
@article{osti_1174907,
title = {Method for indexing and retrieving manufacturing-specific digital imagery based on image content},
author = {Ferrell, Regina K. and Karnowski, Thomas P. and Tobin, Jr., Kenneth W.},
abstractNote = {A method for indexing and retrieving manufacturing-specific digital images based on image content comprises three steps. First, at least one feature vector can be extracted from a manufacturing-specific digital image stored in an image database. In particular, each extracted feature vector corresponds to a particular characteristic of the manufacturing-specific digital image, for instance, a digital image modality and overall characteristic, a substrate/background characteristic, and an anomaly/defect characteristic. Notably, the extracting step includes generating a defect mask using a detection process. Second, using an unsupervised clustering method, each extracted feature vector can be indexed in a hierarchical search tree. Third, a manufacturing-specific digital image associated with a feature vector stored in the hierarchicial search tree can be retrieved, wherein the manufacturing-specific digital image has image content comparably related to the image content of the query image. More particularly, can include two data reductions, the first performed based upon a query vector extracted from a query image. Subsequently, a user can select relevant images resulting from the first data reduction. From the selection, a prototype vector can be calculated, from which a second-level data reduction can be performed. The second-level data reduction can result in a subset of feature vectors comparable to the prototype vector, and further comparable to the query vector. An additional fourth step can include managing the hierarchical search tree by substituting a vector average for several redundant feature vectors encapsulated by nodes in the hierarchical search tree.},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = {2004},
month = {6}
}

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Works referenced in this record:

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A knowledge-based approach for retrieving images by content
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Knowledge-based image retrieval with spatial and temporal constructs
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Hierarchical color clustering for segmentation of textured images
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Indexing pictorial documents by their content: a survey of current techniques
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