Image analysis – Histogram processing – With pattern recognition or classification
Reexamination Certificate
2001-04-04
2004-10-26
Johnson, Timothy M. (Department: 2625)
Image analysis
Histogram processing
With pattern recognition or classification
C348S700000
Reexamination Certificate
active
06810145
ABSTRACT:
FIELD OF THE INVENTION
The invention relates to a process and device for detecting a change of shot in a succession of video images, commonly referred to as a “cut”.
BACKGROUND OF THE INVENTION
The need to tag such changes of shot in an audio-visual sequence arises in particular in frame tempo conversion applications where temporal filtering is generally used. When two consecutive frames are no longer correlated, this filtering is no longer desirable. A prior detection of this change of shot thus makes it possible to utilize another type of interpolation, for example a frame repetition, thus avoiding an inconsistent mix.
Extraction of indexing parameters for video content, segmentation by video shot utilizing prior detection of transitions are also applications of the invention.
The known processes for detecting a change of shot in a video sequence generally rely on the difference in histograms of luminance between the two consecutive frames considered. The principle is therefore based on the variation in luminance from one shot to the next. This type of detector is very sensitive to the variations in luminance which may occur independently of the changes of scene and is not therefore very reliable.
The aim of the invention is to alleviate the aforesaid drawbacks.
SUMMARY OF THE INVENTION
Its object is a process for detecting a change of shot in a succession of video images, comprising a step of creating histograms of an image representing the occurrences of the luminance values as a function of these values, a step of comparing a histogram of an image T(t) with a histogram of a previous image T(t−1), characterized in that the step of comparing consists:
in calculating, for an occurrence histo_lum (n,t) corresponding to a luminance value n in the image T(t), the absolute differences between this occurrence and the occurrences histo_lum (n+k,t−1) of the previous image, k varying from −K to +K, K being a natural integer,
in choosing the minimum value Min_Diff (n,t) from among these differences,
in summing the minimum values for the set of luminance values of the histogram,
in comparing the sum obtained with a threshold.
According to a particular embodiment, the process performs, before the comparing step, a step of filtering the histograms carrying out an averaging of an occurrence relating to a given luminance value n on the basis of occurrences of neighbouring luminance values, the comparing step being performed on the filtered histograms.
One application relates to a process of audio-visual indexation for the extraction of parameters for indexing sequences, this indexation process being characterized in that it comprises a step of detecting a change of shot according to the process of the invention.
The process proposed, although also relying on a histogram difference, makes it possible to absorb variations in luminance which may give rise to false detections. The origins of these variations may typically stem from a zoom, from tracking, for example when entering a shadier zone, from a slight camera movement, etc.
The process proposed is more reliable, more effective and simpler to implement. The corresponding device, which is very economical, can very easily be inserted into mass market apparatus. It is in fact a very good compromise between complexity of construction and effectiveness.
This process can also be part of a more sophisticated audio-visual indexation system for which it may constitute a basic algorithmic block. It may be supplemented with other analysis layers enabling detection to be rendered still more robust.
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Gargi et al., “Peformance Characterization of Video-Shot-Change detection Methods,” IEEE Transactions on Circuits and Systems for Video Technology, vol. 10, No. 1, Feb. 2000, pp. 1-13.*
Fernando et al., “Fade-in and Fade-out detection in Video Sequences using Histograms,” IEEE International Symposium on Circuits and Systems, May 2000, pp. IV709-IV712.*
Dailianas et al., “Comparison of Automatic Video Segmentation Algorithms,” Proc. Integration Issues in Large Commercial Media Delivery Systems, vol. SPIE 2615, Oct. 1995, pp. 2-16.
Babonneau Jean-Yves
Briand Gerard
Verdier Alain
Davenport Francis A.
Fried Harvey D.
Hung Yubin
Johnson Timothy M.
Thomson Licensing S.A.
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