Title :
Automatic image capturing and processing for PetrolWatch
Author :
Dong, Yi Fei ; Kanhere, Salil ; Chou, Chun Tung ; Liu, Ren Ping
Author_Institution :
Univ. of New South Wales, Sydney, NSW, Australia
Abstract :
In our previous work [1], we proposed a Participatory Sensing (PS) architecture called PetrolWatch to collect and share fuel prices from camera images of road-side price board (billboard) of service (or gas) stations. A key part of the PetrolWatch architecture, and the main focus of this paper, is the automatic billboard image capture from a moving car without user intervention. We develop the system design and implementation of the automatic image collection for PetrolWatch. Capturing a clear image by an unassisted mobile phone from a moving car is proved to be a challenge by our street driving experiments. We design the camera control and image pre-selection schemes to address this challenge. In particular, we leverage the advanced capabilities of modern mobile phones to design an acceptable camera triggering range and set the camera focus accordingly. Experiment results show that our design improve fuel price extraction rate by more than 40%. To deal with blurred images caused by vehicle vibrations, we design a set of pre-selection thresholds based on the measures from embedded accelerometer of the mobile phone. Our experiments show that our pre-selection improves the system efficiency by eliminating 78.57% of the blurred images.
Keywords :
image processing; image sensors; mobile computing; traffic engineering computing; PS; PetrolWatch; automatic image capturing; automatic image collection; automatic image processing; blurred images; camera control; camera focus; camera triggering; embedded accelerometer; mobile phone; participatory sensing; road side price board; user intervention; vehicle vibrations; Acceleration; Accelerometers; Cameras; Fuels; Global Positioning System; Mobile handsets; Vibrations; Automatic data collection; Computer-vision-based sensing; Consumer pricing information gathering; Participatory sensor networks; Vehicular sensor networks;
Conference_Titel :
Networks (ICON), 2011 17th IEEE International Conference on
Conference_Location :
Singapore
Print_ISBN :
978-1-4577-1824-3
DOI :
10.1109/ICON.2011.6168481