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@article{145242,
        author = {Jayandrath R. Mangrolia},
        title = {Gabor Feature based Abnormal Event Detection},
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {4},
        number = {8},
        pages = {125-127},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=145242},
        abstract = {In today’s world security in public places, such as airport, railway stations, shopping malls etc is highly essential, that’s why abnormal event detection in video has attracted more attention in the computer vision research community. This paper presents a novel approach for detection of abnormal events and upon detection of such events notification is sent to concerned authority. The proposed algorithm specifies Gabor filter based features used for motion analysis.  Extracted features are given to Artificial Neural Network which is used to recognize whether the input event is normal or abnormal. Proposed algorithm is very much efficient and provides high level of accuracy. },
        keywords = {Abnormal Event Detection, Gabor Filter, Artificial Neural Network},
        month = {},
        }