Automated aircraft instrument reading using real time video analysis

Automated Dial Reading (ADR) using image processing is a challenging task that has to deal with the dynamics of real time environment. Literature contains limited research work for ADR that is based on background subtraction, object tracking, and pattern recognition. These methods suffer from dynamic environment such as: varying light intensity, poor resolution, and vibrations in capturing device. A valuable contribution to the existing dial reading approaches is made in this paper by deploying convolution method which plays a significant role in needle/hand recognition within a dial. Proposed dial reading approach is successfully used and tested reading analogue aircraft instruments facilitated by the Flight Guardian1 (FG) project for automated reading of the cockpit devices in dynamic environments. Performance is evaluated by statistical analysis of the experimental results that proved the robustness of the proposed method.

[1]  Shutao Zhao,et al.  Research on Remote Meter Automatic Reading Based on Computer Vision , 2005, 2005 IEEE/PES Transmission & Distribution Conference & Exposition: Asia and Pacific.

[2]  Pietro Perona,et al.  Object class recognition by unsupervised scale-invariant learning , 2003, 2003 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2003. Proceedings..

[3]  Björn Hemming,et al.  Calibration of dial indicators using machine vision , 2002 .

[4]  Richard Szeliski,et al.  Computer Vision - Algorithms and Applications , 2011, Texts in Computer Science.

[5]  Massimo Piccardi,et al.  Background subtraction techniques: a review , 2004, 2004 IEEE International Conference on Systems, Man and Cybernetics (IEEE Cat. No.04CH37583).

[6]  L. Jetto,et al.  Image registration for applications in Digital Subtraction Angiography , 1998 .

[7]  Isaac N. Bankman,et al.  Handbook of medical imaging , 2000 .

[8]  Max A. Viergever,et al.  A survey of medical image registration , 1998, Medical Image Anal..

[9]  Moussa Souare Efficient Way of Reading Rotary Dial Utility Meter Using Image Processing , 2009 .

[10]  Jun Zhao,et al.  Application Research of Computer Vision in the Auto-Calibration of Dial Gauges , 2008, 2008 International Conference on Computer Science and Software Engineering.

[11]  Richard L. Van Metter,et al.  Handbook of Medical Imaging , 2009 .

[12]  Juan Humberto Sossa Azuela,et al.  Image Processing for Automatic Reading of Electro-Mechanical Utility Meters , 2013, 2013 12th Mexican International Conference on Artificial Intelligence.

[13]  Danko Antolovic,et al.  Review of the Hough Transform Method, With an Implementation of the Fast Hough Variant for Line Detection , 2008 .

[14]  Gurumurthy Swaminathan,et al.  Analog dial gauge reader for handheld devices , 2013, 2013 IEEE 8th Conference on Industrial Electronics and Applications (ICIEA).