Realtimeimageprocessing
- 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 ?