Comparison of Automatic Shot Boundary Detection Algorithms Based On Color, Edges and Wavelets

Gjorgji Madzarov, Suzana Loskovska, Ivica Dimitrovski, Dejan Gjorgjevikj

Abstract: Shot boundary detection is fundamental to video analysis since it segments a video into its basic components. This paper presents a comparison of several shot boundary detection techniques and their variations including color histogram, edge directions histogram and wavelet transformations statistics. The performance and ease of selecting good thresholds for these algorithms are evaluated based on a wide variety of video sequences with different object and camera motions. Threshold selection is performed using sliding window. We used TV news, sports and documentary, music, movie and nature video sequences to estimate the performance of the algorithms. The experimental results indicate that the algorithm based on color histograms is most suitable for shot boundary detection in film and documentary categories, but the algorithm based on wavelet is preferable for nature and sports categories.


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