Method for automatic determination of color-density correction values for the reproduction of digital image data

• US 20040114797A1
• Filed: 10/22/2003
• Published: 06/17/2004
• Est. Priority Date: 12/16/2002
• Status: Abandoned Application

• Current Assignee: Agfa-Gevaert AG (Agfa-Gevaert N.V.)
• Original Assignee: Agfa-Gevaert AG (Agfa-Gevaert N.V.)
• Inventors: Meckes, Guenter
• Application Number:
  US10/691,107
• Publication Number:
  US 20040114797A1
• Time in Patent Office: Days
• US Class Current: 382/167
• CPC Class Codes: G06T 2207/30144 Printing quality
• CPC Class Codes: G06T 2207/30201 Face
• CPC Class Codes: G06T 7/90 Determination of colour characteristics
• CPC Class Codes: G06V 40/18 Eye characteristics, e.g. of the iris
• CPC Class Codes: H04N 1/603 controlled by characteristics of the picture signal generator or the picture reproducer

Abstract

A method for automatic determination of color-density correction values for the reproduction of digital image data, wherein image color-density values of the digital image data are determined at least by area, and are compared with corresponding, known reproduction color-density values. For better results, eye scleras are identified within the image data, and image color-density values are determined from them.

Claims

1. A method for the automatic determination of color-density correction values for the reproduction of digital image data, wherein image color-density values of the digital image data are at least partially determined by area and are compared with known reproduction color-density values, the improvement comprising the steps of identifying eye scleras within the image data, and determining image color-density values based on said scleras.

2. Method as recited claim 1, wherein eye positions are determined by means of a face-detection method in order to identify the scleras.

3. Method as recited in claim 1, wherein eye positions are determined by means of a “

red-eye”

detection method in order to identify the scleras.

4. Method as recited in claim 2, wherein areas of approximately white color are localized in the region of the eye positions in order to identify the scleras.

5. Method as recited in claim 1, wherein the identified scleras are verified based on their surrounding environment.

6. Method as recited in claim 1, wherein the identified scleras are verified based on their color saturation.

7. Method as recited in claim 1, wherein the identified scleras are verified based on their geometric characteristics.

8. Method as recited in claim 1, wherein an area is formed consisting of substantially all points belonging to a sclera.

9. Method as recited in claim 8, wherein substantially all points within the area are used to determine image color-density values of the sclera.

10. Method as recited in claim 1, wherein reproduction color-density values are determined based on statistics of color-density values from a large number of sample eye scleras.

11. Method as recited in claim 1, further comprising the steps of determining color-density correction values in dependence upon said scleras and color-density correction values in dependence upon skin tones, and adjusting the image color-density values based on said color-density correction values.