1. DONE BY :-
V.VAITHILINGAM,III-ECE.
A.GOPINATH, III-ECE.

2. OVERVIEW
 INTRODUCTION
 HARDWARE PLATFORM TO RTIP
 RTIP ON DISTRIBUTED COMPUTER SYSTEMS
 RTIP APPLIED TO TRAFFIC QUEUE
 APPLICATIONS
 CONCLUSION

3. INTRODUCTION
 Image Processing
 Real Time Image Processing
 Real-time in the perceptual sense
 Real-time in the signal processing sense.

4. REAL TIME IMAGE PROCESSING
 What is Real-time Image Processing?
Processing the video signals instantaneously which
have been taken at real time.
 How it differs from ordinary Image Processing?
Image processing means processing the stored
images for improving their quality. But RTIP means
processing the video signals spontaneously.

5. NEEDS OF RTIP
• high resolution, high frame rate video
input
• low latency video input
• low latency operating system scheduling
• high processing performance

6. REAL-TIME IMAGE PROCESSING
 System Design
camera ADC bus driver RTIP display
software
Hardware Selection and Software Performance both are
crucial.

7. SAMPLING RESOLUTION
 What is the need for Sampling Resolution?
 Spatial resolution and temporal resolution are both
crucial
camera ADC bus driver RTIP display

8. LOW LATENCY VIDEO INPUT
 Latency targets
 perceived synchronicity
 Unavoidable latency
 1 to 2 frames(40 - 80ms for PAL)
 Additional latency must be minimized

9. 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.

10. HIGH PROCESSING PERFORMANCE
 Both latency and throughput are important
 PAL video frame: 884Kb
 Sustained data rate: 22Mb/s
 Memory bandwidth is crucial.

11. 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.

12. SOFTWARE OPERATIONS INVOLVED IN RTIP
 Levels of Image Processing:
HIGH -
LEVEL
INTERMEDIATE -LEVEL
LOW-LEVEL

13.  Low-level operations
 Intermediate -level operations
 High-level operations

14. 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 reduction etc.

15. 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.

16. HIGH LEVEL OPERATIONS
 Interpret the abstract data from the intermediate-
level, performing high level knowledge-based
scene analysis on a reduced amount of data.

17. 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

18.  Image analysis system structure: -
RAM backing
CCTV 64kbytes store
ADC
camera
data bus
16-Bit mini-
computers
DAC
Printer
Monitor

19.  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

20.  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.

21. 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

22. EDGE
QUEUE
DETECTION
DETECTION

23. APPLICATIONS
 video conferencing
 augmented reality
 context aware computing
 video-based interfaces for human-computer
interaction

24. 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

25. 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.

26. 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.

27. 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- ment algorithm
has been applied to traffic scenes with different
lighting conditions. And RTIP be at the heart of
many applications.

28. THANK
YOU
?