Method of and system for detecting uniform color segments

• US 7,177,470 B2
• Filed: 11/13/2002
• Issued: 02/13/2007
• Est. Priority Date: 11/13/2002
• Status: Expired due to Fees

• Current Assignee: Koninklijke Philips Electronics N.V. (Koninklijke Philips N.V.)
• Original Assignee: Koninklijke Philips N.V.
• Inventors: Dimitrova, Nevenka, Agnihotri, Lalitha, Jasinschi, Radu Serban
• Primary Examiner(s): Mancuso; Joseph
• Assistant Examiner(s): Ge; Yuzhen
• Application Number:
  US10/294,406
• Publication Number:
  US 20040090453A1
• Time in Patent Office: 1,553 Days
• Field of Search: 382/236
• US Class Current: 382/170
• CPC Class Codes: G11B 27/28 by using information signals recorded by the same method as the main recording G11B27/22 takes precedence
• CPC Class Codes: H04N 11/044 involving transform coding
• CPC Class Codes: H04N 17/02 for colour television signals
• CPC Class Codes: H04N 5/147 Scene change detection
• CPC Class Codes: H04N 9/64 Circuits for processing colour signals H04N9/77 takes precedence; camera processing pipelines for processing colour signals H04N23/84

Abstract

The present invention provides a method of detecting segment boundaries for a series of successive frames in a video sequence. The method includes the steps of acquiring color information from each frame, determining a color histogram for each frame, and applying a boundary detection technique utilizing the color histograms. Finally, the method includes segmenting the frames of the video sequence into uniform color segments. In addition, a system is provided for detecting segment boundaries for a series of successive frames in a video sequence. The system includes means for acquiring color information from each frame, means for determining a color histogram for each frame, and means for applying a boundary detection technique utilizing the color histograms. Finally, the system includes means for segmenting the frames of the video sequence into uniform color segments. The boundary detection techniques include a family color histogram method, a weighted average color histogram method, a successive color histogram method, a stochastic method, a shot-based color histogram method, a mosaic color histogram method, and a computable macro-segment boundary method.

Claims

1. A method of detecting segment boundaries for a series of successive frames in a video sequence comprising:

acquiring color information from each frame;

determining a color histogram for each frame;

applying a boundary detection technique utilizing the color histogram;

segmenting the frames of the video sequence into uniform color segments, wherein the boundary detection technique applied is a weighted average color histogram method, which includes the steps of computing a weighted average color histogram height and a weighted average color histogram height variance; and

computing a weighted average color histogram height variance of the variance.

2. The method of claim 1, wherein the weighted average color histogram height variance of fine variance is based on:

3. The method of claim 2, further comprising the steps of comparing the weighted averages <

v>

_j and <

a>

_j to pre-determined thresholds and determining a new uniform color segment when the weighted averages exceed the pre-determined threshold values.

4. The method of claim 1, wherein at least one of said height and said height variance is iteratively computed from frame to frame.

5. The method of claim 4, wherein said at least one includes said height.

6. The method of claim 4, wherein said at least one includes said height variance.

7. The method of claim 6, wherein said at least one includes both said height and said height variance.

8. The method of claim 1, wherein a Gaussian weight function utilizes at least one of said height and said height variance in said boundary detection technique.

9. The method of claim 8, wherein at least one of said height and said height variance is iteratively computed from frame to frame.

10. A method of detecting segment boundaries for a series of successive frames in a video sequence comprising:

acquiring color information from each frame;

determining a color histogram for each frame;

applying a boundary detection technique utilizing the color histograms; and

segmenting the frames of the video sequence into uniform color segments, wherein the boundary detection technique applied is a weighted average color histogram method, which includes the steps of computing a weighted average color histogram height and a weighted average color histogram height variance;

wherein the weighted average color histogram height is based on;

11. A method of detecting segment boundaries for a series of successive frames in a video sequence comprising:

acquiring color information from each frame;

determining a color histogram for each frame;

applying a boundary detection technique utilizing the color histograms; and

segmenting the frames of the video sequence into uniform color segments, wherein the boundary detection technique applied is a weighted average color histogram method, which includes the steps of computing a weighted average color histogram height and a weighted average color histogram height variance;

wherein the weighted average color histogram height variance is based on;

12. A system for detecting segment boundaries for a series of successive frames in a video sequence comprising:

means for acquiring color information from each frame;

means for determining a color histogram for each frame;

means for applying a boundary detection technique utilizing the color histograms;

means for segmenting the frames of the video sequence into uniform color segments, wherein the boundary detection technique is a weighted average color histogram method, which includes the steps of computing a weighted average color histogram height and a weighted average color histogram height variance and;

means for computing a weighted average color histogram height variance of the varience.

13. The system of claim 12, wherein at least one of said height and said height variance is iteratively computed from frame to frame.

14. The system of claim 13, wherein said at least one includes said height.

15. The system of claim 13, wherein said at least one includes said height variance.

16. The system of claim 13, wherein said at least one includes both said height and said height variance.

17. The system of claim 12, wherein a Gaussian weight function utilizes at least one of said height and said height variance in said boundary detection technique.

18. The system of claim 17, wherein at least one of said height and said height variance is iteratively computed from frame to frame.