Video Surveillance System


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A J2ME-Based Wireless Intelligent Video Surveillance System

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Video Surveillance System

  1. 1. A J2ME-Based WirelessIntelligent Video Surveillance System A.M.Mattash
  2. 2. Contents Introduction J2ME Image processing Background subtraction System alert System architecture Hardware Advantages Conclusion
  3. 3. Introduction Personalized and intelligent use of appliances for the security purpose are necessities in our life today. These appliances tend to be special-purpose, limited- resource, network-connected devices, such as Cell phones. A low cost intelligent wireless security and monitoring solution using moving object recognition technology is presented.
  4. 4. J2ME
  5. 5. Java Editions Java 2 Platform Java2 Java2 Java2Standard Edition Enterprise Edition Micro Edition (J2SE™) (J2EE™) (J2ME™)Standard desktop & Heavy duty server Small & memoryworkstation applications systems constrained devices
  6. 6. Java Editions Each edition defines different sets of class libraries. J2ME provides a robust, flexible environment for application running on a broad range of other deceives J2EE J2SE J2ME
  7. 7. J2ME Core Concepts Configuration  Minimum platform J2ME required for a Profile group of devices Profile J2ME  Addresses specific Libraries needs of a certain Java Language device family Optional Packages Java Virtual Machine Set of APIs in support of additional, common Host Operating System behaviors. E.g. Mobile Media API.
  8. 8. Image processing
  9. 9. Statistics Mean  Center of gravity of the object N N 1 1 x mean xi y mean yi N is the number N i 1 N i 1 of object pixels Variance  The Variance measures the variations of the object-pixels’ positions around the center of gravity N N 1 2 1 2x var ( xi x mean ) y var ( yi y mean ) N i 1 N i 1
  10. 10. Statistics Standard deviation: sigma ( ) x sigma x var How to use it  ”Automatic” thresholding based on statistics Example: the color of the hand  Algorithm:  if: THmin < pixel < Thmax  then: hand pixel  else: non-hand pixel  Training  Average color of hand: mean  Variations in the color of the hand: variance =>  Use statistics: THmin = mean-2 and THmax = mean+2
  11. 11. Segmentation in Video Videos are Image Sequences over Time x • 10 Images • An image is a function t f ( x, y , t ) ft ( x , y ) y • At each time step two have an image f ( x , y ) • Frame rate = the number of images per second
  12. 12. Segmentation using Motion Assuming that only the object is moving => motion can be used to find the object Motion detection We are using Background subtraction algorithm to detect moving object.
  13. 13. Background Subtraction
  14. 14. Background Subtraction Uses a reference background image for comparison purposes. Current image (containing target object) is compared to reference image pixel by pixel. Places where there are differences are detected and classified as moving objects. Motivation: simple difference of two images shows moving objects
  15. 15. a. Original scene b. Same scene laterSubtraction of scene a from scene b Subtracted image with threshold of 100
  16. 16. Background Subtraction Foreground is moving, background is stable Algorithm 1. Capture image containing background 2. Capture N images and calculate the average background image ( Background template) 3. Subtract image (difference = motion) 4. Threshold 5. Delete noise
  17. 17. System Alert
  18. 18. ALERT RECEIVED Alert sent to predefined numberSystem sends alert (SMS, MMS)
  19. 19. System Alert When the system detect moving object, it sets the alert on the Cell phone The system create Message connection, gathering the information required ( address , message text..) Then the message is sent to notify the user
  20. 20. System architecture If the difference between real-time Real Time frame and template Frame Capture reaches predefined threshold, moving Background Subtraction Algorithm object are considered to appear SMS Alert / MMS Alert
  21. 21. Hardware Mobile phone based on J2ME Mobile phone with camera
  22. 22. Advantages1. Low cost surveillance system2. Little memory consumption3. Easy to operate4. Mobility is presented5. Available to wide rang of mobile phones
  23. 23. conclusion This approach is to develop a system which will enable the user to apply security with minimum cost and affords. The system should be able to detect any theft action and alert the user in minimum time.
  24. 24. References IEEE DOI 10.1109/CISP.2008.235 The complete reference J2ME, McGRAW HILL,2006
  25. 25. THANK YOU!Special thanks to Mr. U.B.Kodgule sir