@article{MAKHILLTSS201712224122,
    title = {Key Frame Selection of Video CCTV Segmentation Based on Statistical Model},
    journal = {The Social Sciences},
    volume = {12},
    number = {2},
    pages = {221-226},
    year = {2017},
    issn = {1818-5800},
    doi = {sscience.2017.221.226},
    url = {https://makhillpublications.co/view-article.php?issn=1818-5800&doi=sscience.2017.221.226},
    author = {Wisnu,Mochamad and},
    keywords = {Retrieval,key frame,similarity calculation,segmentation,removed},
    abstract = {Basically, Video CCTV is a collection of frames that are executed in sequence. The frame contains
information of color values that will generate a color histogram values for determining the distance of two
frames. The distance of two frames used to determine the position of the frame in the segment. This research
is done to find the similarity between frames. Research activities are divided into five levels: frame generation,
similarity calculation, shot segmentation, key frame selection and the final generation. Segmentation method
is done by using a statistical model (Histogram difference and sum of absolute difference). Similarities between
the two frames are calculated based on the difference within two frames (Euclidean distance). The similarities
of the two frames will cause excessive frame. Similarities will also bring the same information with the selected
frame (key frame) so it is recommended to be removed.}
    }