Detecting violent scenes in movies using Gated Recurrent Units and Discrete Wavelet Transform


  • Elly Matul Imah Universitas Negeri Surabaya
  • Ivan Kurnia Laksono Universitas Negeri Surabaya
  • Karisma Karisma Universitas Negeri Surabaya
  • Atik Wintarti Universitas Negeri Surabaya



deep learning, gate recurrent unit, violence detection, video processing, wavelet


The easiness of accessing video on various platforms can negatively impact if not done wisely, especially for children. Parental supervision is needed so that movies platforms avoid inappropriate displays such as violence. Violent scenes in movies can trigger children to commit acts of violence, which is not desired. Unfortunately, it is not easy to supervise them fully. This study proposed a method for automatic detection of violent scenes in movies. Automatic violence detection assists the parents and censorship institutions in detecting violence easily. This study uses Gated Recurrent Units (GRU) algorithm and wavelet as feature extraction to detect violent scenes. This paper shows comparative studies on the variation of the mother wavelet. The experimental results show that GRU is robust and deliver the best performance accuracy of 0.96 while combining with mother wavelet Symlet and Coiflets8. The combination of GRU with wavelet Coiflets8 shows better results than the predecessor.

Author Biographies

Elly Matul Imah, Universitas Negeri Surabaya

Department of Mathematics

Ivan Kurnia Laksono, Universitas Negeri Surabaya

Unit of Artificial Intelligence and Scientific Publication

Karisma Karisma, Universitas Negeri Surabaya

Unit of Artificial Intelligence and Scientific Publication

Atik Wintarti, Universitas Negeri Surabaya

Department of Mathematics


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