Abstract
This paper deals with a novel method for knife detection in images. The special feature of any knife is its simple geometric form. The proposed knife detection scheme is based on searching object with corresponding form. Fuzzy and possibilistic shell clustering methods are used to find contours of objects in the picture. These methods give as a result a set of second-degree curves offered in analytical form. To answer the question whether there is a knife in the picture, the angle between two such curves is calculated and its value is estimated. A C++ program was developed for experiments allowing to confirm the suitability of the proposed scheme for knife detection. Robustness of possibilistic c quadric shell clustering to outlier points let us use this algorithm in real-life situations. The objective of research is to use the results for developing a system for monitoring dangerous situation in urban environment using public CCTV systems.
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Maksimova, A. (2013). Knife Detection Scheme Based on Possibilistic Shell Clustering. In: Dziech, A., Czyżewski, A. (eds) Multimedia Communications, Services and Security. MCSS 2013. Communications in Computer and Information Science, vol 368. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-38559-9_13
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DOI: https://doi.org/10.1007/978-3-642-38559-9_13
Publisher Name: Springer, Berlin, Heidelberg
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