@article{MAKHILLAJIT20171666657,
    title = {A New Optimal Feature Selection Scheme with Orthogonal Polynomials and
Ant Colony Optimization for Content Based Video Retrieval System},
    journal = {Asian Journal of Information Technology},
    volume = {16},
    number = {6},
    pages = {383-391},
    year = {2017},
    issn = {1682-3915},
    doi = {ajit.2017.383.391},
    url = {https://makhillpublications.co/view-article.php?issn=1682-3915&doi=ajit.2017.383.391},
    author = {R. and},
    keywords = {Ant Colony Optimization (ACO),CBVRS,feature selection,orthogonal polynomials,optimal,scheme,information},
    abstract = {In this study, a new optimal feature selection scheme with orthogonal polynomials and Ant Colony
Optimization (ACO) for Content-Based Video Retrieval System (CBVRS) is proposed. Initially, the video file is
divided in to smaller number of chunks as shots in orthogonal polynomials transform domain. In order to
identify the key frames to represent a shot, each video image inside a shot is then applied with same orthogonal
polynomials to yield Direct Coefficients (DC) images. In this research, the DC image which has the maximum
DC value is modeled to be a key frame. From the identified key frames, low level feature such as color, edge and
texture information are extracted in the same orthogonal polynomials domain. Since, the extracted features are
larger in size, ACO scheme is adopted to select optimal features that represent a key frame for content-based
video retrieval system.}
    }