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Towards Auto-Extracting
Car Park Structures:
Image Processing
Approach on Low
Powered Devices
Ian K.T.Tan, Poo Kuan Hoong ...
Introduction
Problem
• Time wasted for motorist to search for available car
park space.
– Leads to traffic congestion, wastage of resou...
Research Area
• There have been numerous interests in the
area of detecting availability of car park
bay using image proce...
Extracting Car Park Structures
• Considerable works have been conducted on
extracting car park structures. However, many o...
Method
Actual Image from the System
• Low cost (initial and maintenance)
solution for open space car park using low
powere...
Hardware
• Raspberry Pi Model B+
• Raspberry Pi Camera
• 8GB SD Card
Software
• RaspbianWheezy
• GNU C++ Compiler
• OpenCV...
Image Pro-processing
Original RGB
Image
RGB Grayscale
Conversion
Background
subtraction
Denoise
(smoother
filtering,
thres...
Extraction Method
HoughlineP Algorithm will detect
numerous lines, from which they are
used to determine the corners
A Fit...
Results
• Applied to images downloaded from the
Internet for testing
– Different image sizes
– From approximately “lamp po...
Current Limitations and Conclusion
• Robust solution but is still work in progress to achieve acceptable
consistent accura...
Sample Process
A more detailed output graphically of each stage of the process
Original Image
Binary Image
Pixel SegmentationTechnique
Line Detection
Corner Detection
Linking the Corners
Square Box Mapping
Merged (from multiple cameras) Boxes Mapped to
Original Image
ThankYou
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Towards Auto-Extracting Car Park Structures: Image Processing Approach on Low Powered Devices

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There have been numerous interests in the area of detecting availability of car park bay using image processing techniques instead of utilizing expensive sensors. An area that has been neglected in doing so is the initial calibration of the image capturing device on the need to determine the car park structures. This paper proposes a technique that addresses this issue, using the limited processing capabilities of embedded systems. The results are promising, where in its current form, is semi-automated calibration for the car park structure detection and further enhancements can be made, to make it completely automated

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Towards Auto-Extracting Car Park Structures: Image Processing Approach on Low Powered Devices

  1. 1. Towards Auto-Extracting Car Park Structures: Image Processing Approach on Low Powered Devices Ian K.T.Tan, Poo Kuan Hoong andYap Chin Hong Multimedia University
  2. 2. Introduction
  3. 3. Problem • Time wasted for motorist to search for available car park space. – Leads to traffic congestion, wastage of resources in the process. – Inefficient use of available car parks. • Implementation of digital signages coupled with sensors are expensive and complicated – No effective delivery of this information from car park management to the motorists. – Localized signage, only viewable in the vicinity. • Integrated car park management system for open car park such as recreational parks or stadiums would be unjustifiable
  4. 4. Research Area • There have been numerous interests in the area of detecting availability of car park bay using image processing techniques. • An area that has been neglected in doing so is the initial calibration of the image capturing device. – On determining the car park structures • We propose a technique that attempts to address this issue – using the limited processing capabilities of embedded systems. References 1 – 13.
  5. 5. Extracting Car Park Structures • Considerable works have been conducted on extracting car park structures. However, many of them (Cheng et al., 2014) (Seo & Urmson, 2009) (Tong et al., 2014) (Tschentscher et al, 2013) are from images captured from an aerial view. – This will incur significant cost, and – Unrealistic for commercial implementations • Another approach would be to conduct scene determination using object identification (Felzenszwalb et al., 2010) (Schneiderman & Kanade, 2004). – The computational resource requirements to conduct object identification will not be easily achieved on low powered devices. References 18 - 22. References 23 - 24.
  6. 6. Method Actual Image from the System • Low cost (initial and maintenance) solution for open space car park using low powered devices, – Remove the need of manual mapping of the car park structures for each installation of the camera. – Reduce the need to re-calibrate the device due to movement. • Two main process involved – Pre-processing to produce a binary image, and – Car park structure extraction.
  7. 7. Hardware • Raspberry Pi Model B+ • Raspberry Pi Camera • 8GB SD Card Software • RaspbianWheezy • GNU C++ Compiler • OpenCV 2.4.4 Tools
  8. 8. Image Pro-processing Original RGB Image RGB Grayscale Conversion Background subtraction Denoise (smoother filtering, thresholding, dilation filtering) Binary image output
  9. 9. Extraction Method HoughlineP Algorithm will detect numerous lines, from which they are used to determine the corners A FitLine algorithm is then used to “connect the dots (corners)”. This is done for two axes. From the lines, the FindSquare which is technically find the “trapeziums” in the images and finally a MergeSquare algorithm is applied which is heuristics based on adjacent “squares” that may be a single square.
  10. 10. Results • Applied to images downloaded from the Internet for testing – Different image sizes – From approximately “lamp post” angle – The car park structures of interest are the nearest rows only • Results vary from 25% to greater than 90%
  11. 11. Current Limitations and Conclusion • Robust solution but is still work in progress to achieve acceptable consistent accuracy rates. • Current limitations of the solution – The image has to be taken at approximately right angles in order for the lines to be drawn appropriately. – The angle of the image has to be taken from approximately between 30º to 60º. – The physical car park structure lines demarcations are required. • Future Plans – Multi-camera aggregation method where results from multiple cameras are taken into consideration in order to determine the car park structures. • Initial results shows improvement. – In funding proposal stage for alternative approach.
  12. 12. Sample Process A more detailed output graphically of each stage of the process
  13. 13. Original Image
  14. 14. Binary Image
  15. 15. Pixel SegmentationTechnique
  16. 16. Line Detection
  17. 17. Corner Detection
  18. 18. Linking the Corners
  19. 19. Square Box Mapping
  20. 20. Merged (from multiple cameras) Boxes Mapped to Original Image
  21. 21. ThankYou

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