A real-time wavelet-based video compression approach to intelligent video surveillance systems

Bing Fei Wu*, Yen Lin Chen, Chao Jung Chen, Chung Cheng Chiu, Chorng Yann Su

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

5 Citations (Scopus)


This work presents a wavelet-based approach to compressing video, with high speed, high image quality and high compression ratio. Using the sequential characteristics of surveillance images, this method applies the low-complexity zero-tree coding, which costs low memory, to develop an algorithm for encoding and decoding video, which greatly improves the speeds of compression and decompression and maintains images of high quality. The method provides good quality and smoothness even under multi-channel surveillance, and so is of great value to companies that develop multi-channel surveillance systems. The ActiveX technique is used to implement the algorithm to take advantage of multimedia, the internet and visual rapid-application-development. The versatile and intelligent surveillance system includes peripheral computer hardware and mobile communication. Incorporating IA, this system is not just a surveillance system but is, rather, an intelligent home manager that can control electronic appliances, video/audio systems and home security in an 'e-Home'.

Original languageEnglish
Pages (from-to)50-64
Number of pages15
JournalInternational Journal of Computer Applications in Technology
Issue number1
Publication statusPublished - 2006
Externally publishedYes


  • Low complexity
  • Mobile carrier
  • Real-time
  • Video compression
  • Video surveillance

ASJC Scopus subject areas

  • Software
  • Information Systems
  • Computer Science Applications
  • Computer Networks and Communications
  • Industrial and Manufacturing Engineering
  • Electrical and Electronic Engineering


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