Method for the reduction of image content redundancy in large image libraries
First Claim
1. A method of increasing information content for content-based image retrieval (CBIR) systems, comprising the steps of:
- providing a CBIR database, said database comprising an index for a plurality of stored digital images using a plurality of feature vectors, said feature vectors corresponding to distinct descriptive characteristics of said images;
calculating a visual similarity parameter value based on a degree of visual similarity between features vectors of an incoming image being considered for entry into said database and feature vectors associated with a most similar of said stored images, and determining whether to store or how long to store said feature vectors associated with said incoming image in said database based on said visual similarity parameter value.
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Abstract
A method of increasing information content for content-based image retrieval (CBIR) systems includes the steps of providing a CBIR database, the database having an index for a plurality of stored digital images using a plurality of feature vectors, the feature vectors corresponding to distinct descriptive characteristics of the images. A visual similarity parameter value is calculated based on a degree of visual similarity between features vectors of an incoming image being considered for entry into the database and feature vectors associated with a most similar of the stored images. Based on said visual similarity parameter value it is determined whether to store or how long to store the feature vectors associated with the incoming image in the database.
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Citations
15 Claims
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1. A method of increasing information content for content-based image retrieval (CBIR) systems, comprising the steps of:
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providing a CBIR database, said database comprising an index for a plurality of stored digital images using a plurality of feature vectors, said feature vectors corresponding to distinct descriptive characteristics of said images;
calculating a visual similarity parameter value based on a degree of visual similarity between features vectors of an incoming image being considered for entry into said database and feature vectors associated with a most similar of said stored images, and determining whether to store or how long to store said feature vectors associated with said incoming image in said database based on said visual similarity parameter value. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12)
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13. A content-based image retrieval (CBIR) system, comprising:
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computer apparatus programmed with a routine set of instructions stored in a fixed medium, said computer apparatus comprising;
structure for extracting a plurality of feature vectors from a digital image, said feature vectors corresponding to particular descriptive characteristics of said image;
structure for implementing a clustering method to index said feature vectors into a hierarchical search tree;
a database storing said feature vectors associated with a plurality of said digital images communicably coupled to an image storage manager module, said image storage module identifying a visual similarity parameter value based on a degree of visual similarity between features vectors of an incoming digital image being considered for entry into said database and feature vectors of a most similar of said plurality of said digital images, and determining whether to store or how long to store said incoming said feature vectors associated with said incoming image in said database based on said visual similarity parameter value, and structure for retrieving at least one of said stored images, said structure for retrieving extracting at least one image having feature vectors comparably related to said feature vectors associated with said query image. - View Dependent Claims (14, 15)
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Specification