xinran iain2012 presentation

7/29/2019 Xinran IAIN2012 Presentation

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Ship Draft Detection Based on

Machine VisionRAN Xin, SHI Chaojian, XIAO Baojia

Merchant Marine College, Shanghai Maritime

University, Shanghai, P.R. China2012-10-2


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1 Introduction

Water-borne vesselscan carry largeamounts of cargo

economically It is important to

obtain accuratereadings of the vesseldraft to determine the

amount of cargo thathas been loaded ontothe vessel.


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1 Introduction

The ship draft marksare located at 6specific positionsaround the freeboard.

The marine surveyorswill observe the draftlines and read thenumbers before andafter unloading

cargoes, then usethem to calculate theweight of cargoes.


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1 Introduction

Limits of draftsurvey by manualobservation

Subjective visualestimation leads todifferent results

Conditions onoceans and riverscan drasticallyaffect the draft linemeasurements


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2 Draft survey by machine vision

undetected

detected

Preprocessing

Draft line detection

enhancement

Ship draft calculation

Original ship draft image

Draft mark recognition

Image acquisition

Recognition

Result statistic and display

Draft detection


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2.1 Image acquisition

The original images are taken by surveyor around the ship using camera,then the image data are transferred to the computer to process.


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2.1 Image acquisition

Usually not suitable for direct detection of draft line due toinappropriate position or view angle of surveyor, and also due to theinfluence of sunshine or wave conditions.


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2.2 Image preprocessing

The red, green and blue channel are divided from theoriginal image. It is noticed that the draft line is moredistinct in red channel than in other channels.

So the red channel will be split from the original imageand used at the subsequently step.


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2.3 Edge detection

The results illustrate that the best way to extractingdraft line is Canny operator adopted in red imagechannel.


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2.4 Geometry transformation

An affine transform algorithm is used to adjustthe image making the draft line horizontal.


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2.5 Hough transform

The two longer lines, the draft line and theupper waterline, are detected and illustrated ingreen.


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2.6 Draft line detection

Depending on the common sense that the watermarkline is always at upper position than draft line, the lowerand true draft line will be picked out at the final step.


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3. Draft mark recognition

Binarization

Draft mark

extraction


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3. Draft mark recognition continue

Thin algorithmof mathematicalmorphology.

Draft markrecognitionbased ontrigeminal point

features.


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3. Draft mark recognition continue

Draft markcalculation anddisplay.

Draft markstatistic.


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4. Conclusion

Draft line detection is the first and significantstep for ship draft survey.

In order to overcome the limits of the traditionalship draft survey methods, an automaticrecognition system based on machine vision ispresented.

The experimental results show that theproposed system is effective and can be usedinstead of visual observation.


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Thank You!

xinran iain2012 presentation

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