Dynamic test pattern composition for image-analysis based automatic machine diagnostics

• US 20050286742A1
• Filed: 06/28/2004
• Published: 12/29/2005
• Est. Priority Date: 06/28/2004
• Status: Active Grant

• Current Assignee: Xerox Corporation (Xerox Holdings Corp.)
• Original Assignee: Xerox Corporation (Xerox Holdings Corp.)
• Inventors: Dalal, Edul N., Sampath, Meera, Rasmussen, D. Rene
• Granted Patent: US 7,773,774 B2
• Time in Patent Office: Days
• US Class Current: 382/112
• CPC Class Codes: B41J 29/393 Devices for controlling or analysing the entire machine ; Controlling or analysing mechanical parameters involving printing of test patterns
• CPC Class Codes: H04N 1/00002 Diagnosis, testing or measuring; Detecting, analysing or monitoring not otherwise provided for error detection, error correction or monitoring in digital computers or digital computer components G06F11/00
• CPC Class Codes: H04N 1/00005 relating to image data
• CPC Class Codes: H04N 1/00015 Reproducing apparatus
• CPC Class Codes: H04N 1/00018 Scanning arrangements
• CPC Class Codes: H04N 1/00034 Measuring, i.e. determining a quantity by comparison with a standard H04N1/00031 takes precedence
• CPC Class Codes: H04N 1/00045 using a reference pattern designed for the purpose, e.g. a test chart
• CPC Class Codes: H04N 1/0005 in service, i.e. during normal operation
• CPC Class Codes: H04N 1/00063 using at least a part of the apparatus itself, e.g. self-testing
• CPC Class Codes: H04N 1/00068 Calculating or estimating
• CPC Class Codes: H04N 1/00087 Setting or calibrating picture signal circuits H04N1/40

Abstract

The present invention is directed to a system and method for test target selection in conjunction with dynamic test pattern generation. In the invention, a test pattern page(s) is composed using an optimal set of test targets, which can be accommodated or adjusted to fit within size constraints of the test pattern. The method of the present invention makes use of layout optimization to ensure that related and optimized test targets are accommodated on a single test pattern. For example, it may be preferable to “squeeze in” a smaller-than-normal uniform area target, rather than not to print it at all during a test.

Claims

1. A method for dynamic test pattern generation, including the steps of:

automatically selecting a set of test targets as a function of the probability of possible defects and machine performance data and to maximize an optimization criteria; and

placing the set of test targets on a digital test pattern.

2. The method of claim 1, further including the step of performing a test target layout optimization such that additional test targets within the set of test targets can be accommodated on a single test pattern.

3. The method of claim 1, wherein the step of automatically selecting a set of test targets in accordance with an optimal test target sequence includes selecting a test target from memory.

4. The method of claim 3, wherein the step of selecting a test target from memory is facilitated by a look-up table containing test target characteristics.

5. The method of claim 1, wherein the step of automatically selecting a next test target is a constrained optimization process wherein the optimization criteria is to maximize the discriminating power between the defects detectable by the test targets.

6. The method of claim 1, wherein the step of automatically selecting a set of test targets includes consideration of any requirement for combining test targets within the set of test targets on a common test pattern, and selecting the test targets if adequate space is available to print the test targets.

7. The method of claim 1, wherein the step of automatically selecting a set of test targets includes setting specific characteristics of at least one test target.

8. The method of claim 1, wherein the optimization criteria minimizes the time taken to reach a diagnosis.

9. The method of claim 1, wherein the optimization criteria minimizes the overall cost of running the diagnostic system.

10. The method of claim 1, wherein at least a portion of the machine performance data is obtained as a result of feedback from an analysis of a previously printed test pattern.

11. The method of claim 1, wherein the step of automatically selecting a set of test targets further includes the steps of:

(a) automatically selecting a test target in accordance with an optimal test target sequence, wherein the sequence is a function of the probability of possible defects and machine performance data;

(b) placing the test target on a digital test pattern;

(c) automatically selecting a next test target in accordance with the optimal test target sequence, wherein the next test target is one that can be accommodated on remaining space of the test pattern;

(d) placing the next test target on the digital test pattern; and

(e) repeating steps (c) and (d) until no additional test targets are accommodated on the test pattern

12. A method for automated image quality based diagnostics and remediation of a document processing system, including the steps of:

selecting, as a function of potential defects, at least one of a plurality of test targets for output as a test pattern by the document processing system;

generating a printed output of the test pattern;

obtaining data pertaining to the document processing system, including scanning the printed output to obtain image data pertaining to the output of the at least one selected test target; and

analyzing the data to obtain an initial diagnosis, the diagnosis including at least one potential defect as identified in data corresponding to the at least one selected test target, and including performing an image quality analysis of the data corresponding to the data for the at least one selected test target.

13. The method of claim 12, further including the step of refining the initial diagnosis by selecting, as a function of the initial diagnosis, another of the plurality of test targets for output by the document processing system;

generating a printed output of the selected test target;

obtaining data pertaining to the document processing system, including scanning the printed output to obtain image data pertaining to the output of the selected test target; and

analyzing the data to obtain a refined diagnosis, the diagnosis including at least one potential defect as identified in data corresponding to the selected patterns.

14. The method of claim 12, wherein said step of selecting at least one of the plurality of test targets for output further includes identifying, as a function of possible defects, at least one test target that will provide a visual indication of such a defect so as to cause the identified test target to be rendered as an output of the document processing system.

15. The method of claim 14, wherein the selection of test targets is further based upon the probability of a possible defect.

16. The method of claim 14, wherein specific characteristics of the test target are also determined as a function of the possible defects.

17. The method of claim 16, wherein the specific characteristics of the test target include at least the size of the test target and its location on the test pattern.

18. The method of claim 12, wherein said step of selecting at least one of the plurality of test targets further includes identifying, as a function of possible defects, a plurality of test targets that will provide a visual indication of a plurality of defects so as to cause the identified test targets to be rendered on a common test pattern as an output of the document processing system.

19. A system for automated image quality based diagnosis of a document processing system, comprising:

a test selection module, including a dynamic test target selection function, so as to select at least one of a plurality of test targets as a function of a diagnostic request to produce a test pattern;

a print engine, operatively associated with the document processing system, for rendering the test pattern;

an image quality analysis module that identifies and characterizes defects within a test target on the test pattern produced by print engine and generates key features of the defects for further analysis; and

a diagnostic engine that analyzes the data generated by the image quality analysis module to obtain a diagnosis, the diagnosis including at least one diagnosis from a list of potential defects in data corresponding to at least one test pattern image, wherein the diagnostic engine refines the initial diagnosis based on the at least one identified defect.

20. The system of claim 19, wherein said test selection module operates automatically in response to machine data, wherein said data is indicative of the status of at least one subsystem of the document processing system as determined from a sensor associated therewith.