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

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. Introduction

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. 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. 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. 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. Hardware
• Raspberry Pi Model B+
• Raspberry Pi Camera
• 8GB SD Card
Software
• RaspbianWheezy
• GNU C++ Compiler
• OpenCV 2.4.4
Tools

8. Image Pro-processing
Original RGB
Image
RGB Grayscale
Conversion
Background
subtraction
Denoise
(smoother
filtering,
thresholding,
dilation filtering)
Binary image
output

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. 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. 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. Sample Process
A more detailed output graphically of each stage of the process

13. Original Image

14. Binary Image

15. Pixel SegmentationTechnique

16. Line Detection

17. Corner Detection

18. Linking the Corners

19. Square Box Mapping

20. Merged (from multiple cameras) Boxes Mapped to
Original Image

21. ThankYou