HEURISTIC METHOD FOR DROP FRAME DETECTION IN DIGITAL BASEBAND VIDEO

• US 20140016038A1
• Filed: 05/28/2013
• Published: 01/16/2014
• Est. Priority Date: 05/28/2012
• Status: Abandoned Application

• Current Assignee: Project Giants, LLC
• Original Assignee: Tektronix Incorporated (Fortive Corp.)
• Inventors: Ramaswamy, Krishna Seshadri, Karegoudar, Malateshgouda V.
• Application Number:
  US13/903,615
• Publication Number:
  US 20140016038A1
• Time in Patent Office: Days
• US Class Current: 348/700
• CPC Class Codes: G06T 2207/20021 Dividing image into blocks, subimages or windows
• CPC Class Codes: G06T 2207/30168 Image quality inspection
• CPC Class Codes: G06T 7/0002 Inspection of images, e.g. flaw detection
• CPC Class Codes: H04N 17/004 for digital television systems
• CPC Class Codes: H04N 19/89 involving methods or arrangements for detection of transmission errors at the decoder
• CPC Class Codes: H04N 5/147 Scene change detection

Abstract

A video detector for detecting dropped frames in a video according to embodiments of the invention may include a quality measurer structured to generate a quality measure of a transition between a current frame and a previous frame, a dynamic threshold generator structured to generate a threshold value based on a comparison of blocks within the current frame, and an identifier structured to indicate the video as having a dropped frame based on a comparison between the difference value and the threshold value. Methods of performing dropped frame detection in a video stream are also described.

Claims

1. A video detector for detecting dropped frames in a video that includes a number of individual sequential frames, each frame made from a number of individual blocks, the detector comprising:

an input for accepting the video;

a quality measurer structured to generate a quality measure of a transition between a current frame and a previous frame;

a dynamic threshold generator structured to generate a threshold value based on a comparison of blocks within the current frame; and

an identifier structured to indicate the video as having a dropped frame based on a comparison between the difference value and the threshold value.

2. The video detector for detecting dropped frames according to claim 1 in which the quality measurer is a Structural Similarity Index Metric (SSIM) calculator.

3. The video detector for detecting dropped frames according to claim 1 in which the dynamic threshold generator is structured to compare an SSIM of sub-frame blocks of the current frame to a measure of similarity for the compared sub-frame block.

4. The video detector for detecting dropped frames according to claim 3 in which the dynamic threshold generator is further structured to compare the SSIM of sub-frame blocks of the current frame to a measure of dissimilarity for the compared sub-frame block.

5. The video detector for detecting dropped frames according to claim 4 in which the measure of similarity and the measure of dissimilarity are empirically derived.

6. The video detector for detecting dropped frames according to claim 1, further comprising a scene change detector structured to determine if there was a scene change between the first frame and the second frame.

7. The video detector for detecting dropped frames according to claim 6, in which, when the scene change detector determines that there was a scene change between the first frame and the second frame, the video detector is structured to cause the quality measurer and dynamic threshold generator to not generate values for the current frame.

8. A method for detecting dropped video frames in a stream of video frames, the method comprising:

determining a quality measure of a transition in a video to a current frame from a previous frame;

comparing the quality measure to a threshold difference level; and

indicating that there is a dropped frame in the stream of video frames when the quality measure meets or exceeds the threshold difference level.

9. The method for detecting dropped video frames in a stream of video frames according to claim 8, in which determining a quality measure of a transition comprises generating a Structural Similarity Index Metric (SSIM).

10. The method for detecting dropped video frames in a stream of video frames according to claim 8, further comprising:

determining whether there was a scene change between the current frame and the previous frame.

11. The method for detecting dropped video frames in a stream of video frames according to claim 8, further comprising:

generating the threshold difference level.

12. The method for detecting dropped video frames in a stream of video frames according to claim 11 in which generating the threshold difference level comprises generating a dynamic threshold level.

13. The method for detecting dropped video frames in a stream of video frames according to claim 12, in which:

generating the dynamic threshold level comprises comparing an SSIM of a plurality of sub-frame blocks of the current frame to a measure of similarity for the compared sub-frame block.

14. The method for detecting dropped video frames in a stream of video frames according to claim 13, further comprising:

comparing the SSIM of a plurality of sub-frame blocks of the current frame to a measure of dissimilarity for the compared sub-frame block.