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Real Time Image Processing
 

Real Time Image Processing

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Seminar presented by Soniya Kumari of SOE,CUSAT.

Seminar presented by Soniya Kumari of SOE,CUSAT.

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    Real Time Image Processing Real Time Image Processing Presentation Transcript

    • REAL TIME IMAGE PROCESSING
      From research to reality
      GUIDE:SHEENA S
      By:
      SONIYA KUMARI
    • OVERVIEW
      INTRODUCTION
      HARDWARE PLATFORM TO RTIP
      RTIP ON DISTRIBUTED COMPUTER SYSTEMS
      RTIP APPLIED TO TRAFFIC QUEUE
      APPLICATIONS
      CONCLUSION
    • INTRODUCTION
      • Image Processing
      • Real Time
      • Real-time in the perceptual sense
      • Real-time in the software engineering
      sense.
      • Real-time in the signal processing sense.
    • Real Time Image Processing
      • What is Real-time Image Processing?
      • How it differs from ordinary Image Processing?
      • What is the need for RTIP?
    • camera
      ADC
      driver
      RTIP
      display
      bus
      software
      Real-Time Image Processing
      System Design
      Haredware Selection and Software Performance both are crucial.
    • Real-Time Image Processing
      • Platform Requirements:
      • high resolution, high frame rate video
      input
      • low latency video input
      • low latency operating system scheduling
      • high processing performance
    • Sampling Resolution
      • What is the need for Sampling Resolution?
      • Spatial resolution and temporal resolution are both crucial
      camera
      ADC
      driver
      RTIP
      display
      bus
    • Low Latency Video Input
      Latency targets
      perceived synchronicity
      Unavoidable latency
      1 to 2 frames(40 - 80ms for PAL)
      Additional latency must be minimized
    • Low Latency Operating System Scheduling
      Processing of video signals depend on
      -video capture hardware in use.
      -driver component.
      Software components has crucial impact on system latency.
      To avoid loss of input data, buffering is introduced to cover lag.
      Mac OS X has excellent low latency performance.
    • High Processing Performance
      Both latency and throughput are important
      PAL video frame: 884Kb
      Sustained data rate: 22Mb/s
      Memory bandwidth is crucial.
      AltiVec is very useful .
    • MAC OS X
      Mac OS X is the world’s most advanced operating system.
      • Features:
      Power of unix simplicity of MAC.
      Perfect integration of hardware and software.
      Elegant interface and stunning graphics.
      Highly secure by design.
      Innovation for everyone.
      Reliable to the core.
    • Software Operations Involved In RTIP
      • Levels of Image Processing:
      HIGH -LEVEL
      INTERMEDIATE -LEVEL
      LOW-LEVEL
      • Low-level operations
      • Intermediate -level operations
      • High-level operations
    • Low level Operations
      • Low-level operators take an image as their input and produce an image as their output.
      • It transform image data to image data i.e it
      deal directly with image matrix data at the pixel level.
      • Examples:-color transformations, gamma correction, linear or nonlinear filtering, noise reductionetc.
      • Goal of Low Level Operation.
    • Intermediate Level Operations
      • It transform image data to a slightly more abstract form of information by extracting certain attributes of image.
      • Ultimate goal is to reduce the amount of data to form a set of features suitable for further high-level processing.
      • Examples:-segmentation of image into regions/objects of interest, extracting edges etc.
    • High Level operations
      • It interpret the abstract data from the intermediate-level, performing high level knowledge-based scene analysis on a reduced amount of data.
      • They are less data intensive and more inherently sequential rather than parallel.
    • RTIP Applied On Traffic-Queue Detection Algorithm
      • Why RTIP applied to traffic?
      -For reducing congestion problem
      • Need for processing of traffic data
      -Traffic control
      -Traffic management
      -Road safety
      -Development of transport policy.
      • Traffic measurable parameters
      -Traffic volumes & Speed
      -Inter-vehicle gaps & Vehicle classification
    • Image analysis system structure: -
      backing
      store
      data bus
      RAM
      64kbytes
      CCTV
      camera
      ADC
      16-Bit mini-computers
      DAC
      Printer
      Monitor
    • Stages of image analysis:-
      • Image sensors used
      • ADC Conversion
      • Pre-processing
      To cope with this, two methods are proposed:
      1. Analyze data in real time – uneconomical
      2. Stores all data and analyses off-line at low speed
    • Two jobs to be done:
      Green light on: - determine no. of vehicles moving along particular lanes and their classification by shape and size.
      Red light on: - determine the backup length along with the possibility to track its dynamics and classify vehicles in backup.
    • QUEUE DETECTION ALGORITHM
      • Spatial-domain technique is used to detect queue – implemented in real-time using low-cost system.
      • For this purpose two different algorithms have been used:-
      • Motion detection operation
      • Vehicle detection operation
    • QUEUEDETECTION
      EDGE DETECTION
    • APPLICATIONS
      • video conferencing
      • augmented reality
      • context aware computing
      • video-based interfaces for human-computer interaction
    • VIDEO CONFERENCING
      It is digital compression of audio and video streams in real time.
      Video input : video camera or webcam.
      Video output: computer monitor television or projector
    • AUGMENTED REALITY
      A combination of a real scene viewed by a user and a virtual scene generated by a computer that augments the scene with additional information.
    • CONTEXT AWARE COMPUTING
      A system is context-aware if it uses context to provide relevant information and/or services to the user, where
      relevancy depends on
      the user’s task.
    • CONCLUSION
      RTIP involves many aspects of hardware and software in order to achieve high resolution input,low latency capture,high performance processing and efficient display.The measure- mentalgorithm has been applied to traffic scenes with different lighting conditions. And RTIP be at the heart of many applications.
    • THANK YOU
      ?