Colour Histogram and Modified Multi-layer Perceptron Neural Network based Video Shot Boundary Detection
DaltonThounaojam1,
Thongam Khelchandra2, Thokchom Jayshree2, Sudipta Roy3,
and Khumanthem Singh2
1Department of Computer Science and Engineering, National
Institute of Technology Silchar, India
2Department of Computer Science and Engineering, National
Institute of Technology Manipur, India
3Department
of Computer Science and Engineering, Assam University Silchar, India
Abstract: The paper
proposes a shot boundary detection technique using colour histogram difference
and modified Multi-Layer Perceptron (MLP). In this the learning process in the
MLP is modified as an evolutionary learning process using Genetic Algorithm
(GA) in which the weights of the hidden layer and output layer of the MLP are
updated by GA. Colour Histogram Differences (HD) between two consecutive frames
are used for feature extraction. Four values HDi,HDi-1
and-1 are used as an input for the modified MLP Neural Network where HDi is the colour histogram difference between frame fi
and fi+1, HDi-1 is the colour histogram difference
between frame fi-1 and fi and HDi+1 is the colour
histogram difference between frame fi+1 and fi+2. The
propose system is tested with the TRECVid 2001 and 2007 test data and it is
also compared with latest algorithms and yields better results.
Keywords: Abrupt;
fade-in; fade-out; dissolve; shot boundary detection; neural network; genetic algorithm.
Received February 11, 2016; accepted March 26, 2017