MSU Scene Change Detector (SCD)

Common Description

Scene Change Detector is made to automatic identification of scene boundaries in video sequence.

Change Log

[!] — Known bug
[+] — New Feature
[*] — Other

Version 1.2
[*] Windows Vista & Windows 7 support implemented

Version 1.1
[*] Visualization bug fixed for non-stadard resolution video

Version 1.0
[+] First plugin release


The plugin implements four algorithms of similarity measurements between two adjacency frames in video sequence:

  1. Pixel-level frames comparison
  2. Global Histogram comparison
  3. Block-Based Histogram comparison
  4. Motion-Based similarity measure

The choice of the algorithm can be made in Settings. Numbers from 1 up to 4 corresponds to each algorithm.

Default and recommended value is 3 (Block-Based Histogram).


Y-plane is drawing during the visualization. Brightness of scene boundary frames is increased.

Example of visualization:


Metric’s plot is making after all measurements. “One” value means that current frame is the first frame in scene, other frames have “zero” values. Sequence average value is the number of detected scene changes.

Plot's example
Plot's example


Pixel-level comparison

Similarity measure of two frames is the sum of absolute differences (SAD) between corresponding pixels values.

Global Histogram

The histogram is obtained by counting the number of pixels in frame with specified brightness level. The difference between two histograms is then determined calculating SAD of number of pixels on each brightness level.

Block-Based Histogram

Each frame is divided into 16x16 pixel blocks. Brightness distribution histogram is constructed for each block. Then similarity measure for each block is obtained. Average value of these measures is accepted as a frames similarity measure.


Motion Estimation algorithm with block size 16x16 pixels is performed for two adjacency frames at the first stage. After that average value of motion vector errors is accepted as a finally similarity measure.




10 May 2017
See Also
MSU Video Upscalers Benchmark 2021
The most comprehensive comparison of video super resolution (VSR) algorithms by subjective quality
MSU Video Quality Measurement Tool: Picture types
VQMT 13.1 Online help: List of all picture types available in VQMT and their aliases
MSU Video Quality Measurement Tool: Usage of VQMT metrics in CLI
VQMT 13.1 Online help: Description of VQMT metrics, their parameters and using in CLI
MSU Video Quality Measurement Tool: VQMT various lists and tables
VQMT 13.1 Online help: Information about VQMT visualization formats, read modes, etc...
MSU Video Quality Measurement Tool: Command-line help
VQMT 13.1 Online help: Information about all VQMT CLI options for Pro/Premium versions
MSU Video Quality Measurement Tool: Configuration description
VQMT 13.1 Online help: Description of the format of the VQMT configuration file
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