Colour Histogram and Modified Multi-layer Perceptron Neural Network based Video Shot Boundary Detect

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

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