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Real-time analysis of fuel spray images

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1 Author(s)
Badreldin, A. ; General Motors Research Laboratories, Warren, Michigan

This paper provides a fast and efficient technique for real-time preprocessing and analysis of fuel spray images. The preprocessing stage consists of global thresholding of the log-edge of the image. The recognition of in-focus droplets is achieved through a 3-level tree classifier. The algorithm was tested using 400 images including approximately 8000 candidate objects. The percentage of correct classification was > 93%. The algorithm was also tested using 200 images of very low quality, and a recognition rate of 87% was achieved.

Published in:

Acoustics, Speech, and Signal Processing, IEEE International Conference on ICASSP '87.  (Volume:12 )

Date of Conference:

Apr 1987