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An Approach to Robust Visual Knife Detection

Kmiec M., Glowacz A.

Machine Graphics and Vision

2011

Vol. 20, No. 2

215-227

Computerised monitoring of CCTV images is attracting a lot of attention both from potential end-users seeking to increase the effectiveness of their video surveillance systems and as a popular research topic as new methods and algorithms are being developed. In this paper an approach to detecting knives in images is presented. It is based on the use of Histograms of Oriented Gradients (HOG), feature descriptors invariant to geometric and photometric transformations except for rotation. We introduce a dataset containing images of knives in different backgrounds and in varying lighting conditions and evaluate the performance of an HOG-based SVM classifier. We study the question of creating a detector based on knife blade colour and discuss the use of GPU parallel computing as a method of speeding up the detection process.