• Sajad Mohamadzadeh University of Birjand
  • Hassan Farsi University of Birjand



Content based video retrieval (CBVR), hadamard matrix and discrete wavelet transform (HDWT), key frame extraction, shot boundary detection, sparse representation


Video retrieval has recently attracted a lot of research attention due to the exponential growth of video datasets and the internet. Content based video retrieval (CBVR) systems are very useful for a wide range of applications with several type of data such as visual, audio and metadata. In this paper, we are only using the visual information from the video. Shot boundary detection, key frame extraction, and video retrieval are three important parts of CBVR systems. In this paper, we have modified and proposed new methods for the three important parts of our CBVR system. Meanwhile, the local and global color, texture, and motion features of the video are extracted as features of key frames. To evaluate the applicability of the proposed technique against various methods, the P(1) metric and the CC_WEB_VIDEO dataset are used. The experimental results show that the proposed method provides better performance and less processing time compared to the other methods.

Author Biographies

Sajad Mohamadzadeh, University of Birjand

End of Shahid Avini Street, Pardis Shokatabad, Department of Electronics and Communications Engineering, University of Birjand, Birjand, Iran

Hassan Farsi, University of Birjand

End of Shahid Avini Street, Pardis Shokatabad, Department of Electronics and Communications Engineering, University of Birjand, Birjand, Iran


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How to Cite

Mohamadzadeh, S., & Farsi, H. (2016). CONTENT BASED VIDEO RETRIEVAL BASED ON HDWT AND SPARSE REPRESENTATION. Image Analysis and Stereology, 35(2), 67–80.



Original Research Paper