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Proceedings Paper

Research on CCD visual sensor-based embedded level measuring system for oil tankers
Author(s): Le Song; Yu-chi Lin; Mei-rong Zhao; Ying Wu
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Paper Abstract

A new level measuring system for oil tankers based on machine vision is designed for realizing close-cabin operating and remote monitoring. The system adopts ARM9 S3C2240 microchip as the central processing unit. With a high-precision macro-focusing CCD sensor and an image capturing module, the system can acquire the level ruler images and process them with a series of algorithms. Pre-processing procedures to the captured ruler images, including binarizing and denoising methods, are implemented to improve the image quality. A grey level projecting program is used to extract the rectangular area containing digit characters and segment the digits into individual parts. Following judgment strategies are executed to separate the exact digit of the characters. Each character is scanned with vertical and horizontal lines at various positions. Pixel change point numbers are counted to distinguish different digit characters to proceed the recognition procedure. The scale in the viewing field can be accurately localized, so that the automatic recognition result is obtained. The experimental results for different oil levels indicate that the measuring accuracy of this system can achieve ±0.1 mm and the automatic reading time is less than 0.5 s, which shows the characteristics of high-precision and high-speed.

Paper Details

Date Published: 6 August 2009
PDF: 7 pages
Proc. SPIE 7384, International Symposium on Photoelectronic Detection and Imaging 2009: Advances in Imaging Detectors and Applications, 73840W (6 August 2009); doi: 10.1117/12.835044
Show Author Affiliations
Le Song, Tianjin Univ. (China)
Yu-chi Lin, Tianjin Univ. (China)
Mei-rong Zhao, Tianjin Univ. (China)
Ying Wu, Tianjin Univ. (China)


Published in SPIE Proceedings Vol. 7384:
International Symposium on Photoelectronic Detection and Imaging 2009: Advances in Imaging Detectors and Applications
Kun Zhang; Xiang-jun Wang; Guang-jun Zhang; Ke-cong Ai, Editor(s)

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