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Real time image processing ppt

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dear friends this ppt hope will definately help to enhance your knowledge about real time image processing

dear friends this ppt hope will definately help to enhance your knowledge about real time image processing

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  • 1. REAL TIME IMAGEPROCESSING Guided by Prof. K.S. Ingle Student name Ashwini Jagdhane. M.E. (EC)
  • 2. Contents Introduction Literature survey Requirements Difference between real and non real time processing General detection system System design Advantages Disadvantages Applications Future scope Definitions in RTIP in different sense References
  • 3. Introduction•What is Real-time Image Processing?•How it differs from ordinary ImageProcessing?•What is the need for Real time imageprocessing?
  • 4. REAL TIME PROCESSING VS NON REALTIME PROCESSINGReal time processing Non real time processing  Is continuous  Is non continuous  Also called interactive  Also called as batch processing processing  Have deadlines  Not have deadlines  Have predictable response  Extended over time period time  In batch processing missed  With soft real-times, missing a deadlines might mean that the deadline indicates that the computer needs more system is not working at its processing capacity to finish peak tasks.
  • 5. Literature survey Vehicle detection system Speed controller Image recognition with hardware neural networks Real time yahoo! store order processing
  • 6. Vehicle detection system
  • 7. General vehicle detection system
  • 8. Wireless vehicle detection system
  • 9. Image recognition with hardware neural networks
  • 10. Non real synthesis When the processing of sound is first calculated entirely and saved to an audio file (which can be listened to later) one speaks of non-realtime or offline synthesis.
  • 11. Real time synthesis When the stream of data goes directly to the audio interface as it is processed, so that there are only few milliseconds between the processing and the listening of the synthesized sound, one speaks of realtime synthesis.
  • 12. Real time yahoo! Store order processing
  • 13. General detection system
  • 14. Image analysis system structure
  • 15. System design
  • 16. Real-Time Image Processing PlatformRequirements:• High resolution, high frame rate videoinput• Low latency video input• Low latency operating system scheduling• High processing performance
  • 17. Sampling resolution Image processing attempts to extract information from the outside world through its visual appearance. Therefore adequate information must be provided to the processing algorithm by the video input hardware. Broadcast video provides a practical reference point as most cameras provide images in formats derived from broadcast standards regardless of their computer interface (analog, USB etc).
  • 18. Advantages 1. Customer can see the results immediately. 2. Allows you to automate your business. This is especially important if your time is very limited. 3. Real-time image processing also helps eliminate customer errors. 4. Real-time image processing is fast . 5. Real-time image processing is continuous.
  • 19. DisadvantagesCauses many errors when many people code together on the same document. There are chances that they use the same variables for different tasks. In some cases infrared cameras used to detect the object having low pixel capability. Therefore object identification fails.
  • 20. Applications Deriving a compact representation. Includes spatial or temporal down-sampling. Spatial block partitioning. Region of interest or selective processing. Formulating the algorithm in a multi resolution or processing framework. Mobile robots. Video-based interfaces for human computer interaction.
  • 21. Definitions of RTIP in different sense Real-time in the perceptual sense It is used mainly to describe the interaction between a human and a computer device for a near instantaneous response of the device to an input by a human user. For instance, Bovik defines the concept of “real-time” in the context of video processing, describing that “the result of processing appears effectively „instantaneously‟ (usually in a perceptual sense) once the input becomes available”.
  • 22. Definitions of RTIP in different sense Real-time in the signal processing sense It is based on the idea of completing processing in the time available between successive input samples. An important item of note here is that one way to gauge the “real-time” status of an algorithm is to determine some measure of the amount of time it takes for the algorithm to complete all requisite transferring and processing of image data, and then making sure that it is less than the allotted time for processing.
  • 23. Future scope The performance requirements of image processing applications have continuously increased the computing power of implementation platforms, especially when they are executed under real time constraints. The real time applications may consist of different image standards, or different algorithms used at different stages of the processing chain. The computing paradigm using reconfigurable architectures promises an intermediatetrade-off between flexibility and performance.
  • 24. REFERENCES http://www.scribd.com/doc/6738837/Real-Time-Image-and-Video-Processing- From-Research-to-Reality (First Edition 10 9 8 7 6 5 4 3 2 1 Printed in the United States of America) http://www.authorstream.com/Presentation/pl_arun-360868-image-processing- ip-arunpl-science -technology-ppt-power point Rourke , A., and Bell, M.G.H.: „Queue detection and congestion monitoring using mage processing‟, Traffic Engg. and Control A. Bovik, Introduction to Digital Image and Video Processing, in Handbook of Image &VideoProcessing, A. C. Bovik, Ed., Elsevier AcademicPress, 2005 http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2678783/ Real-time processing for Fourier domain optical coherence tomography using a field programmable gate array Grueger, H., R. Gottfried-Gottfried, M. Schwarzenberg, M. Scholles and R. Zachmann, 2001. Magnetic trac detection using fluxgate sensors. Proc. Int. Conf. Sensor, 2: 351-356
  • 25. QUERY?????
  • 26. THANK YOU!!!