realtimeimageprocessing
Post on 24-May-2015
2.321 Views
Preview:
TRANSCRIPT
REAL TIME IMAGE PROCESSING
DONE BY :-
V.VAITHILINGAM,III-ECE.
A.GOPINATH, III-ECE.
OVERVIEWINTRODUCTION
HARDWARE PLATFORM TO RTIP
RTIP ON DISTRIBUTED COMPUTER SYSTEMS
RTIP APPLIED TO TRAFFIC QUEUE
APPLICATIONS
CONCLUSION
INTRODUCTION
Image Processing
Real Time Image Processing
Real-time in the perceptual sense Real-time in the signal processing
sense.
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.
• high resolution, high frame rate video input • low latency video input
• low latency operating system scheduling
• high processing performance
NEEDS OF RTIP
REAL-TIME IMAGE PROCESSING
System Design
Hardware Selection and Software Performance both are crucial.
camera ADC driver RTIP displaybus
software
SAMPLING RESOLUTION
What is the need for Sampling Resolution?
Spatial resolution and temporal resolution are both crucial
camera ADC driver RTIP displaybus
LOW LATENCY VIDEO INPUT
Latency targets
perceived synchronicity
Unavoidable latency1 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.
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:
LOW-LEVEL
INTERMEDIATE -LEVEL
HIGH -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 reduction etc.
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
Interpret the abstract data from the intermediate-level, performing high level knowledge-based scene analysis on a reduced amount of data.
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
CCTVcamera
ADC
RAM64kbytes
16-Bit mini-computers
Printer
DAC
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- ment algorithm has been applied to traffic scenes with different lighting conditions. And RTIP be at the heart of many applications.
THANK
YOU
?
top related