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US 8,477,372 B2Granted
Updating an image quality metric database to account for printer drift
AssigneeXerox Corporation
InventorsWencheng Wu, Edul N. Dalal
Life of this patent
Estimating the term…
Abstract
What is disclosed is a novel system and method for determining a printer metric in terms of image quality (IQ) over a large complex set of conditions based upon measurements taken over a small simple set of conditions while compensating for printer drift. The present system and method effectively utilizes a predictive model that predicts noise measurements of multi-separations from those of single-separation colors and/or a subset of the multi-separations. Because a model is used to comprehend the metric over the entire gamut, the number of patches is reduced. This reduction enables the method to be used within a machine to dynamically characterize the device's image quality metric. Various embodiments have been disclosed.
Claims24
A method for updating an image quality metric database, the method comprising:
- performing at a first time:
- measuring a defined image quality metric for a set of device-dependent colorant specifications;
- storing said measured image quality metric to a database;
- deriving a first model based upon said measurements obtained for the defined image quality metric, corresponding to a subset of said device-dependent colorant specifications;
- using the first model to obtain first model-predicted values for the defined image quality metric at the set of device-dependent colorant specifications;
- determining an error term at each of said set of device-dependent colorant specifications for said defined image quality metric, said error term being a difference between said measured image quality metric and said first model-predicted values;
- and
- storing said set of error terms to said database;
- and
- performing at a second time:
- measuring said defined image quality metric for said subset of device-dependent colorant specifications;
- deriving a second model based upon these measurements performed at said second time;
- using said second model to obtain second model-predicted values for said defined image quality metric;
- adding said set of error terms to said second model-predicted values to produce modified model-predicted values;
- and
- updating said database with said modified model-predicted values.
13 more elements
A system for updating an image quality metric database, said system comprising:
- a memory;
- a storage medium for storing data;
- and
- a processor in communication with said storage medium and said memory, said processor executing machine readable instructions for performing the method of:
- performing at a first time:
- measuring a defined image quality metric for a set of device-dependent colorant specifications;
- storing said measured image quality metric to a database;
- deriving a first model based upon said measurements obtained for the defined image quality metric, corresponding to a subset of said device-dependent colorant specifications;
- using the first model to obtain first model-predicted values for the defined image quality metric at the set of device-dependent colorant specifications;
- determining an error term at each of said set of device-dependent colorant specifications for said defined image quality metric, said error term being a difference between said measured image quality metric and said first model-predicted values;
- and
- storing said set of error terms to said database;
- and
- performing at a second time:
- measuring said defined image quality metric for said subset of device-dependent colorant specifications;
- deriving a second model based upon these measurements performed at said second time;
- using said second model to obtain second model-predicted values for said defined image quality metric;
- adding said set of error terms to said second model-predicted values to produce modified model-predicted values;
- and
- updating said database with said modified model-predicted values.
17 more elements
A method for updating an image quality metric database, the method comprising:
- for at least two time periods performing the following:
- measuring a defined image quality metric for a set of device-dependent colorant specifications;
- storing said measured image quality metric to a database;
- deriving a first variance model based upon said measurements obtained for said defined image quality metric, corresponding to a subset of said device-dependent colorant specifications, wherein said first model comprises a variance model;
- using said first model to obtain first model-predicted values for said defined image quality metric at said set of device-dependent colorant specifications;
- determining an error term at each of said set of device-dependent colorant specifications for said defined image quality metric, said error term being a difference between said measured image quality metric and said first model-predicted values;
- and
- storing said set of error terms to said database;
- and
- performing at a second time:
- measuring said defined image quality metric for said subset of device-dependent colorant specifications;
- deriving a second model based upon these measurements performed at said second time, wherein said second model comprises a variance model;
- using said second model to obtain second model-predicted values for said defined image quality metric at said set of device-dependent colorant specifications;
- adding said set of error terms to said second model-predicted values to produce modified model-predicted values;
- and
- updating said database with said modified model-predicted values.
13 more elements
Dependencies are inferred from the claim text.