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    <title>UTas ePrints - Flexible shape models for image analysis in an automated lobster catch assessment system</title>
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    <meta content="Knights, Mark S." name="eprints.creators_name" />
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<meta content="Management of fisheries is an evolving science combining multiple techniques and strategies.  The involvement of the computer in industry management and research continues to grow.  The area of image analysis is currently limited but continues to grow as computing equipment becomes faster and cheaper.  Locating a particular object in an image and processing information about that object is a significant task that requires a great deal of processing power and finesse.  The benefits of a functioning automated task that processes data on an object, such as a lobster, simply by processing an image of that object would greatly enhance the ability to manage a fishery with accurate, up to date data.

The Tasmanian Aquaculture and Fisheries Institute (TAFI) intend to create a lobster-sorting tray, which can be used on lobster fishing vessels as standard equipment.  This tray would include functionality to take an image of the current lobster and estimate its sex and weight from pertinent measurements on the lobster.  This research demonstrates that through the use of the Active Shape Modeller (ASM) these details can be identified and processed from an image of the lobster.  

The ASM is used within an image analysis process, which can be fully automated, to draw out the required salient details of a lobster from an area of interest in the images.  A series of experiments showed that the ASM was able to draw out and fully identify 77.3% images in a test set of 216 images.  These images then had pertinent lengths and a sex estimated based on these measurements where 90% of the matched lobsters were sexed correctly." name="eprints.abstract" />
<meta content="2007-11-05" name="eprints.date" />
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<meta content="Bhanu, B &amp; Lee, S 1994, Genetic Learning for Adaptive Image Segmentation, Kluwer Academic Publishers, Norwell, Massachusetts.
Bowyer, KW &amp; Phillips, PJ (eds) 1998, Empirical evaluation techniques in computer vision, The Institute of Electrical and Electronics Engineers Inc., Los Alamitos, California.
Chen, P &amp; Suter, D 2006, 'An Analysis of Linear Subspace Approaches for Computer Vision and Pattern Recognition', International Journal of Computer Vision, vol. 68, no. 1, pp. 83 - 106.
Cootes, TF, Edwards, GJ &amp; Taylor, CJ 2001, 'Active appearance models', IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 23, no. 6, pp. 681 - 685.
Cootes, TF &amp; Taylor, CJ 2001, 'On representing edge structure for model matching', paper presented to IEEE Computer Society Conference on Computer Vision and Pattern Recognition, Hawaii.
Cootes, TF &amp; Taylor, CJ 2004, 'Statistical Models of Appearance for Medical Image Analysis and Computer Vision', University of Manchester.
Cootes, TF, Taylor, CJ, Cooper, DH &amp; Graham, J 1995, 'Active Shape Models - Their Training and Application', Computer Vision and Image Understanding, vol. 61, no. Issue 1, pp. pp 38 - 59.
Davies, RH, Twining, CJ, Cootes, TF, Waterton, JC &amp; Taylor, CJ 2002, 'A minimum description length approach to statistical shape modelling', IEEE Transactions on Medical Imaging, vol. 21, no. 5, pp. 525 - 537.
FRDC 2007, R&amp;D Priorities, Fisheries Research and Development Corporation FRDC, viewed 27/10/2007 2007, <www.frdc.com.au/research/priorities/ >.
Frusher, PS, Eaton, L &amp; Bradshaw, M 2003, Impact of management change to an ITQ system in the Tasmanian Rock Lobster fishery, Tasmanian Aquaculture &amp; Fisheries Institute, Hobart.
Frusher, PS, Mackinnon, C &amp; Phillips, A 2003, Assessment of broad scale exploitation rates and biomass estimates for the Tasmanian Southern Rock Lobster fishery, 1997/101, Tasmanian Aquaculture &amp; Fisheries Institute, Hobart.
Frusher, S 2007, Improving profitability and sustainability in the Tasmanian rock lobster fishery.
Frusher, S, Williams, R, Jiang, D &amp; Trellogen, R 2006, 'FRDC R&amp;D Funding Application', University of Tasmania.
Gardner, C, MacDiarmid, A, Mills, D, Oliver, M &amp; Stewart, R 2004, Rock lobster enhancement and aquaculture subprogram: evaluating the release and survival of juvenile rock lobsters released for enhancement purposes, Tasmanian Aquaculture &amp; Fisheries Institute, Hobart.
Gonzalez, RC, Woods, RE &amp; Eddins, SL 2004, Digital Image Processing Using MATLAB, Pearson Prentice Hall, Upper Saddle River, New Jersey.
Gray, JS 1997, Marine Biodiversity: patterns threats and conservation needs, 62, GESAMP, London.
Hamarneh, G 1999, Advanced Shape Modeller in MATLAB, July 19, 2004 edn.
Hamlaoui, S &amp; Davoine, F 2005, 'Facial action tracking using particle filters and active appearance models', paper presented to Joint conference on Smart objects and ambient intelligence: innovative context-aware services: usages and technologies, Grenoble, France.
Haralick, RM &amp; Shapiro, LG 1992, Computer and Robot Vision, vol. 1, 2 vols., Addison-Wesley Publishing Company, Inc., Reading, Massachusetts.
Haralick, RM &amp; Shapiro, LG 1993, Computer and Robot Vision, vol. 2, 2 vols., Addison-Wesley Publishing Company, Inc., Reading, Massachusetts.
Haton, J-P (ed.) 1987, Fundamentals in computer understanding:  speech and vision, Cambridge University Press, Cambridge.
Ikeuchi, K &amp; Veloso, M (eds) 1997, Symbolic Visual Learning, Oxford University Press Inc., New York.
Kelsall, A 2005, 'Flexible Shape Models For Marine Animal Detection', Honours thesis, University of Tasmania.
Kimball, S &amp; Mattis, P 2007, GNU Image Manipulation Program, Version 2.2.8 edn.
Latecki, LJ 1998, Discrete Representation of Spatial Objects in Computer Vision, Kluwer Academic Publishers, Dordrecht, Netherlands.
McClanahan, T &amp; Castilla, JC (eds) 2007, Fisheries Management: Progress toward sustainability, Blackwell Publishing Ltd., Oxford, UK.
Megrey, BA &amp; Moksness, E (eds) 1996, Computers in Fisheries Research, Chapman &amp; Hall, London.
Mikalsen, KH, Hernes, H-K &amp; Jentoft, S 2007, 'Leaning on user-groups: The role of civil society in fisheries governance', Marine Policy, vol. Vol. 31, no. no. 2, pp. pp. 201-209.
Parker, JR 1997, Algorithms for image processing and computer vision, John Wiley and Sons, Inc., New York.
Punt, AE &amp; Kennedy, RB 1997, 'Population modelling of Tasmanian rock lobster, Jasus edwardsii, resources', Marine Freshwater Research, vol. 48, no. 8, pp. pp. 967-980.
Sanz, JLC (ed.) 1996, Image Technology Advances in Image Processing, Multimedia and Machine Vision, Springer-Verlag Berlin, Heidelberg.
Saragih, J &amp; Goecke, R 2006, 'Learning active appearance models from image sequences', paper presented to HCSNet workshop on Use of vision in human-computer interaction.
Singh, A, Goldgof, D &amp; Terzopoulos, D 1998, Deformable Models in Medical Image Analysis, IEEE Computer Society, Los Alamitos, California.
TAFI 2007, The Tasmanian Aquaculture and Fisheries Institute Website, viewed 11 May 2007, <http://www.utas.edu.au/tafi/About.html>.
Umbaugh, SE 2005, Computer imaging : digital image analysis and processing The CRC Press, Boca Raton, Florida.
Walters, CJ, Hall, N, Brown, R &amp; Chubb, C 1993, 'Spatial model for the population dynamics and exploitation of the western Australian rock lobster, Panulirus cygnus .' Canadian Journal of Fisheries and Aquatic Sciences, vol. 50, no. 8, pp. pp. 1650 - 1662.
Ward, T &amp; Hegerl, E 2003, Marine Protected Areas in Ecosystem-based Management of Fisheries, Department of the Environment and heritage, Canberra.
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<meta content="Management of fisheries is an evolving science combining multiple techniques and strategies.  The involvement of the computer in industry management and research continues to grow.  The area of image analysis is currently limited but continues to grow as computing equipment becomes faster and cheaper.  Locating a particular object in an image and processing information about that object is a significant task that requires a great deal of processing power and finesse.  The benefits of a functioning automated task that processes data on an object, such as a lobster, simply by processing an image of that object would greatly enhance the ability to manage a fishery with accurate, up to date data.

The Tasmanian Aquaculture and Fisheries Institute (TAFI) intend to create a lobster-sorting tray, which can be used on lobster fishing vessels as standard equipment.  This tray would include functionality to take an image of the current lobster and estimate its sex and weight from pertinent measurements on the lobster.  This research demonstrates that through the use of the Active Shape Modeller (ASM) these details can be identified and processed from an image of the lobster.  

The ASM is used within an image analysis process, which can be fully automated, to draw out the required salient details of a lobster from an area of interest in the images.  A series of experiments showed that the ASM was able to draw out and fully identify 77.3% images in a test set of 216 images.  These images then had pertinent lengths and a sex estimated based on these measurements where 90% of the matched lobsters were sexed correctly." name="DC.description" />
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    <h1 class="ep_tm_pagetitle">Flexible shape models for image analysis in an automated lobster catch assessment system</h1>
    <p style="margin-bottom: 1em" class="not_ep_block"><span class="person_name">Knights, Mark S.</span> (2007) <xhtml:em>Flexible shape models for image analysis in an automated lobster catch assessment system.</xhtml:em> Honours thesis, University of Tasmania.</p><p style="margin-bottom: 1em" class="not_ep_block"></p><table style="margin-bottom: 1em" class="not_ep_block"><tr><td valign="top" style="text-align:center"><a onmouseover="EPJS_ShowPreview( event, 'doc_preview_4236' );" onmouseout="EPJS_HidePreview( event, 'doc_preview_4236' );" href="http://eprints.utas.edu.au/3013/2/1_front_Knights.pdf"><img alt="[img]" src="http://eprints.utas.edu.au/style/images/fileicons/application_pdf.png" border="0" class="ep_doc_icon" /></a><div class="ep_preview" id="doc_preview_4236"><table><tr><td><img alt="" src="http://eprints.utas.edu.au/3013/thumbnails/2/preview.png" border="0" class="ep_preview_image" /><div class="ep_preview_title">Preview</div></td></tr></table></div></td><td valign="top"><a href="http://eprints.utas.edu.au/3013/2/1_front_Knights.pdf"><span class="ep_document_citation">PDF (Front Matter)</span></a> - Requires a PDF viewer<br />171Kb</td></tr><tr><td valign="top" style="text-align:center"><a onmouseover="EPJS_ShowPreview( event, 'doc_preview_4237' );" onmouseout="EPJS_HidePreview( event, 'doc_preview_4237' );" href="http://eprints.utas.edu.au/3013/3/2_chap1.pdf"><img alt="[img]" src="http://eprints.utas.edu.au/style/images/fileicons/application_pdf.png" border="0" class="ep_doc_icon" /></a><div class="ep_preview" id="doc_preview_4237"><table><tr><td><img alt="" src="http://eprints.utas.edu.au/3013/thumbnails/3/preview.png" border="0" class="ep_preview_image" /><div class="ep_preview_title">Preview</div></td></tr></table></div></td><td valign="top"><a href="http://eprints.utas.edu.au/3013/3/2_chap1.pdf"><span class="ep_document_citation">PDF (Chapter 1)</span></a> - Requires a PDF viewer<br />120Kb</td></tr><tr><td valign="top" style="text-align:center"><a onmouseover="EPJS_ShowPreview( event, 'doc_preview_4238' );" onmouseout="EPJS_HidePreview( event, 'doc_preview_4238' );" href="http://eprints.utas.edu.au/3013/4/3_chap2.pdf"><img alt="[img]" src="http://eprints.utas.edu.au/style/images/fileicons/application_pdf.png" border="0" class="ep_doc_icon" /></a><div class="ep_preview" id="doc_preview_4238"><table><tr><td><img alt="" src="http://eprints.utas.edu.au/3013/thumbnails/4/preview.png" border="0" class="ep_preview_image" /><div class="ep_preview_title">Preview</div></td></tr></table></div></td><td valign="top"><a href="http://eprints.utas.edu.au/3013/4/3_chap2.pdf"><span class="ep_document_citation">PDF (Chapter 2)</span></a> - Requires a PDF viewer<br />319Kb</td></tr><tr><td valign="top" style="text-align:center"><a onmouseover="EPJS_ShowPreview( event, 'doc_preview_4317' );" onmouseout="EPJS_HidePreview( event, 'doc_preview_4317' );" href="http://eprints.utas.edu.au/3013/5/4_Chap3_Knights.pdf"><img alt="[img]" src="http://eprints.utas.edu.au/style/images/fileicons/application_pdf.png" border="0" class="ep_doc_icon" /></a><div class="ep_preview" id="doc_preview_4317"><table><tr><td><img alt="" src="http://eprints.utas.edu.au/3013/thumbnails/5/preview.png" border="0" class="ep_preview_image" /><div class="ep_preview_title">Preview</div></td></tr></table></div></td><td valign="top"><a href="http://eprints.utas.edu.au/3013/5/4_Chap3_Knights.pdf"><span class="ep_document_citation">PDF (Chapter 3)</span></a> - Requires a PDF viewer<br />1213Kb</td></tr><tr><td valign="top" style="text-align:center"><a onmouseover="EPJS_ShowPreview( event, 'doc_preview_4318' );" onmouseout="EPJS_HidePreview( event, 'doc_preview_4318' );" href="http://eprints.utas.edu.au/3013/6/5_Chap4-refs_Knights.pdf"><img alt="[img]" src="http://eprints.utas.edu.au/style/images/fileicons/application_pdf.png" border="0" class="ep_doc_icon" /></a><div class="ep_preview" id="doc_preview_4318"><table><tr><td><img alt="" src="http://eprints.utas.edu.au/3013/thumbnails/6/preview.png" border="0" class="ep_preview_image" /><div class="ep_preview_title">Preview</div></td></tr></table></div></td><td valign="top"><a href="http://eprints.utas.edu.au/3013/6/5_Chap4-refs_Knights.pdf"><span class="ep_document_citation">PDF (Chapter 4, 5 and References)</span></a> - Requires a PDF viewer<br />417Kb</td></tr><tr><td valign="top" style="text-align:center"><a onmouseover="EPJS_ShowPreview( event, 'doc_preview_4319' );" onmouseout="EPJS_HidePreview( event, 'doc_preview_4319' );" href="http://eprints.utas.edu.au/3013/7/6_appendices_Knights.pdf"><img alt="[img]" src="http://eprints.utas.edu.au/style/images/fileicons/application_pdf.png" border="0" class="ep_doc_icon" /></a><div class="ep_preview" id="doc_preview_4319"><table><tr><td><img alt="" src="http://eprints.utas.edu.au/3013/thumbnails/7/preview.png" border="0" class="ep_preview_image" /><div class="ep_preview_title">Preview</div></td></tr></table></div></td><td valign="top"><a href="http://eprints.utas.edu.au/3013/7/6_appendices_Knights.pdf"><span class="ep_document_citation">PDF (Appendices)</span></a> - Requires a PDF viewer<br />83Kb</td></tr></table><div class="not_ep_block"><h2>Abstract</h2><p style="padding-bottom: 16px; text-align: left; margin: 1em auto 0em auto">Management of fisheries is an evolving science combining multiple techniques and strategies.  The involvement of the computer in industry management and research continues to grow.  The area of image analysis is currently limited but continues to grow as computing equipment becomes faster and cheaper.  Locating a particular object in an image and processing information about that object is a significant task that requires a great deal of processing power and finesse.  The benefits of a functioning automated task that processes data on an object, such as a lobster, simply by processing an image of that object would greatly enhance the ability to manage a fishery with accurate, up to date data.&#13;
&#13;
The Tasmanian Aquaculture and Fisheries Institute (TAFI) intend to create a lobster-sorting tray, which can be used on lobster fishing vessels as standard equipment.  This tray would include functionality to take an image of the current lobster and estimate its sex and weight from pertinent measurements on the lobster.  This research demonstrates that through the use of the Active Shape Modeller (ASM) these details can be identified and processed from an image of the lobster.  &#13;
&#13;
The ASM is used within an image analysis process, which can be fully automated, to draw out the required salient details of a lobster from an area of interest in the images.  A series of experiments showed that the ASM was able to draw out and fully identify 77.3% images in a test set of 216 images.  These images then had pertinent lengths and a sex estimated based on these measurements where 90% of the matched lobsters were sexed correctly.</p></div><table style="margin-bottom: 1em" border="0" cellpadding="3" class="not_ep_block"><tr><th valign="top" class="ep_row">Item Type:</th><td valign="top" class="ep_row">Thesis (Honours)</td></tr><tr><th valign="top" class="ep_row">Subjects:</th><td valign="top" class="ep_row"><a href="http://eprints.utas.edu.au/view/subjects/280500.html">280000 Information, Computing and Communication Sciences &gt; 280500 Data Format</a><br /><a href="http://eprints.utas.edu.au/view/subjects/300700.html">300000 Agricultural, Veterinary and Environmental Sciences &gt; 300700 Fisheries Sciences</a><br /><a href="http://eprints.utas.edu.au/view/subjects/280300.html">280000 Information, Computing and Communication Sciences &gt; 280300 Computer Software</a><br /><a href="http://eprints.utas.edu.au/view/subjects/280200.html">280000 Information, Computing and Communication Sciences &gt; 280200 Artificial Intelligence and Signal and Image Processing</a></td></tr><tr><th valign="top" class="ep_row">Collections:</th><td valign="top" class="ep_row">UNSPECIFIED</td></tr><tr><th valign="top" class="ep_row">ID Code:</th><td valign="top" class="ep_row">3013</td></tr><tr><th valign="top" class="ep_row">Deposited By:</th><td valign="top" class="ep_row"><span class="ep_name_citation">Unnamed user with email <a href="mailto:mknights@utas.edu.au">mknights@utas.edu.au</a></span></td></tr><tr><th valign="top" class="ep_row">Deposited On:</th><td valign="top" class="ep_row">01 Feb 2008 09:43</td></tr><tr><th valign="top" class="ep_row">Last Modified:</th><td valign="top" class="ep_row">01 Feb 2008 09:43</td></tr><tr><th valign="top" class="ep_row">ePrint Statistics:</th><td valign="top" class="ep_row"><a target="ePrintStats" href="/es/index.php?action=show_detail_eprint;id=3013;">View statistics for this ePrint</a></td></tr></table><p align="right">Repository Staff Only: <a href="http://eprints.utas.edu.au/cgi/users/home?screen=EPrint::View&amp;eprintid=3013">item control page</a></p>
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