Method and system for detecting transitional markers such as uniform fields in a video signal

• US 5,778,108 A
• Filed: 06/07/1996
• Issued: 07/07/1998
• Est. Priority Date: 06/07/1996
• Status: Expired due to Term

• Current Assignee: Hewlett-Packard Development Company, L.P. (HP Inc.)
• Original Assignee: Electronic Data Systems Corporation (Perspecta, Inc.)
• Inventors: Coleman, Jr., E. North
• Primary Examiner(s): Boudreau, Leo
• Assistant Examiner(s): Novik, Dmitry A.
• Application Number:
  US08/660,641
• Time in Patent Office: 760 Days
• Field of Search: 382/305, 382/306, 382/272, 382/273, 348/699, 348/700, 348/701, 395/328, 395/806, 395/807
• US Class Current: 382/305
• CPC Class Codes: H04N 19/179 the unit being a scene or a shot
• CPC Class Codes: H04N 19/87 involving scene cut or scene change detection in combination with video compression
• CPC Class Codes: H04N 5/147 Scene change detection
• CPC Class Codes: H04N 5/265 Mixing

Abstract

A method and system for detecting transitional markers such as uniform images in a digital video signal made up of a series of video images is disclosed. One aspect of the invention is a method for detecting uniform fields. The method comprises segmenting a plurality of the video images into a number of cells, each cell comprising a number of pixels, each pixel associated with an intensity value representing the intensity of the pixel. Then, a plurality of cell contrast vectors each associated with one of the segmented video images is generated. Each element of the cell contrast vector is associated with one of the cells of the video image and comprises the standard deviation of the pixel intensity values for the pixels in that cell. A uniform image is detected for a video image in response to the cell contrast vector for that image.

Claims

1. A method of detecting a uniform image in a digital video signal made up of a series of video images, comprising:

segmenting a plurality of the video images, each of the plurality of video images segmented into a first number of cells, each cell comprising a second number of pixels, a pixel having a pixel intensity value representing the intensity of the pixel;

generating a plurality of cell contrast vectors each associated with one of the segmented video images, each element of the cell contrast vector associated with one of the cells and comprising the standard deviation of the pixel intensity values for the pixels in that cell;

calculating the maximum cell contrast for each of the segmented video images, the maximum cell contrast for an image comprising the value of the largest element of the cell contrast vector for that image;

generating a plurality of cell intensity vectors each associated with one of the segmented video images, each element of the cell intensity vector associated with one of the cells and comprising the average of the pixel intensity values for the pixels in that cell;

calculating the maximum cell intensity for each of the segmented video images, the maximum cell intensity for an image comprising the value of the largest element of the cell intensity vector for that image; and

generating a blank image detect signal for a video image if the maximum cell intensity for that video image is below a first threshold and the maximum cell contrast for that video image is below a second threshold.

2. The method of claim 1, wherein each video image comprises a field of a video signal.

3. The method of claim 1, wherein each video image comprises a frame of a video signal.

4. A computerized system for detecting a uniform image in a digital video signal made up of a series of video images, comprising:

a computer-readable medium;

a computer program encoded on the computer-readable medium, the computer program operable to

segment a plurality of the video images, each of the plurality of video images segmented into a first number of cells, each cell comprising a second number of pixels, a pixel having a pixel intensity value representing the intensity of the pixel;

generate a plurality of cell contrast vectors each associated with one of the segmented video images, each element of the cell contrast vector associated with one of the cells and comprising the standard deviation of the pixel intensity values for the pixels in that cell;

calculate the maximum cell contrast for each of the segmented video images, the maximum contrast for an image comprising the value of the largest element of the cell contrast vector for that image;

generate a plurality of cell intensity vectors each associated with one of the segmented video images, each element of the cell intensity vector associated with one of the cells and comprising the average of the pixel intensity values for the pixels in that cell;

calculate the maximum cell brightness for each of the segmented video images, the maximum brightness for an image comprising the value of the largest element of the cell intensity vector for that image; and

generate a blank image detect signal for a video image if the maximum cell brightness for that video image is below a first threshold and the maximum cell contrast for that video image is below a second threshold.

5. The computerized system of claim 4, wherein each video image comprises a field of a video signal.

6. The computerized system of claim 4, wherein each video image comprises a frame of a video signal.

7. A computerized system for detecting video events in a digital video signal made up of a series of video images, comprising:

a computer-readable medium; and

a computer program encoded on the computer-readable medium, the computer program further operable to

segment a plurality of the video images, each of the plurality of video images segmented into a first number of cells, each cell comprising a second number of pixels, a pixel having a pixel intensity value representing the intensity of the pixel;

generate a plurality of cell contrast vectors each associated with one of the segmented video images, each element of the cell contrast vector associated with one of the cells and comprising the standard deviation of the pixel intensity values for the pixels in that cell;

generate a cut-detect signal for a video image in response to the change in cell contrast vector for that video image relative to a second video image in said series, the cut-detect signal indicating an abrupt transition from one camera shot to another in the digital video signal; and

generate a blank image detect signal for a video image in response to the cell contrast vector for that video image, the blank image detect signal indicating a blank image in the digital video signal.

8. The computerized system of claim 7, the computer program further operable to:

generate a plurality of cell intensity vectors each associated with one of the segmented video images, each element of the cell intensity vector associated with one of the cells and comprising the average of the pixel intensity values for the pixels in that cell;

generate a fade-detect signal for a segmented video image in response to the change in cell intensity vector for that image relative to a second video image in said series, the fade detect signal indicating a transition between a scene and a uniform image in the digital video signal.

9. The computerized system of claim 7, the computer program further operable to:

generate a dissolve-detect signal for a segmented video image in response to the change in cell contrast vector for that image relative to a second video image in said series, the dissolve-detect signal indicating a transition from a first camera shot to a second camera shot in the digital video signal, the transition comprising a plurality of video images comprising a weighted average of the first and second camera shots.

10. The computerized system of claim 7, the computer program further operable to:

generate a plurality of cell intensity vectors each associated with one of the segmented video images, each element of the cell intensity vector associated with one of the cells and comprising the average of the pixel intensity values for the pixels in that cell;

calculate the maximum cell intensity for each of the segmented video images, the maximum cell intensity for an image comprising the value of the largest element of the cell intensity vector for that image; and

generate a blank image detect signal for a video image if the maximum cell brightness for that video image is below a third threshold and the maximum cell contrast for that video image is below a fourth threshold.

11. The computerized system of claim 7, the computer program further operable to:

generate a plurality of inter-image similarity values each associated with one of the segmented video images, the inter-image similarity signal for a video image comprising the cosine of the angle between the cell contrast vector for that video image and the cell contrast vector for another video image;

generate five run length values by processing the inter-image similarity values, each run length value associated with one of five finite state machines having five states--A, B, C, D, and E, each state machine initialized in a unique one of the five states and with a run length value of zero, the five states connected in a ring, a state transition occurring each time an inter-image similarity value is computed and processed by the state machine, the run length increasing by one in states A and D, the run length increasing by one in states B, C, and E if the inter-image similarity value being processed exceeds a threshold, the run length being reset to zero if the inter-image similarity value is less than the threshold;

compute a combined run length comprising the maximum run length value; and

generate a film-detect signal if the combined run length value exceeds a seventh threshold.

12. The computerized system of claim 8, the computer program further operable to:

generate a dissolve-detect signal for a segmented video image in response to the change in cell contrast vector for that image relative to a second video image in said series, the dissolve-detect signal indicating a transition from a first camera shot to a second camera shot in the digital video signal, the transition comprising a plurality of video images comprising a weighted average of the first and second camera shots.

13. The computerized system of claim 12, the computer program further operable to:

calculate the maximum cell intensity for each of the segmented video images, the maximum cell intensity for an image comprising the value of the largest element of the cell intensity vector for that image; and

generate a blank image detect signal for a video image if the maximum cell brightness for that video image is below a third threshold and the maximum cell contrast for that video image is below a fourth threshold.

14. The computerized system of claim 13, the computer program further operable to:

generate a plurality of inter-image similarity values each associated with one of the segmented video images, the inter-image similarity signal for a video image comprising the cosine of the angle between the cell contrast vector for that video image and the cell contrast vector for another video image;

generate five run length values by processing the inter-image similarity values, each run length value associated with one of five finite state machines having five states--A, B, C, D, and E, each state machine initialized in a unique one of the five states and with a run length value of zero, the five states connected in a ring, a state transition occurring each time an inter-image similarity value is computed and processed by the state machine, the run length increasing by one in states A and D, the run length increasing by one in states B, C, and E if the inter-image similarity value being processed exceeds a threshold, the run length being reset to zero if the inter-image similarity value is less than the threshold;

compute a combined run length comprising the maximum run length value; and

generate a film-detect signal if the combined run length value exceeds a seventh threshold.