<!-- * Set USERSTYLEURL = %PUBURLPATH%/%WEB%/DokumentFormat/fonts.css --> ---+!! Course %FORMFIELD{"Bezeichnung"}% %TOC{depth="3"}% %STARTSECTION{"no_toc"}% --- *Responsible:* Prof. Dr. Thieling ---++ Course ---+++ Meets requirements of following modules(MID) * in active programs * [[BaET2012_IBA]] * [[BaMT2012_BV2]] * [[BaTIN2012_IBA]] * [[BaET2010_IndustrielleBildverarbeitung_2]] * [[MaTIN2010_IndustrielleBildverarbeitung_2]] ---+++ Course Organization <sticky> <table border="0"> <tr valign="top"> <td> <table border="1" cellpadding="2" cellspacing="0"> <th colspan="2">Version</th> <tr> <td>created</td> <td>2011-10-14</td> </tr> <tr> <td>VID</td> <td>1</td> </tr> <tr> <td>valid from</td> <td>WS 2012/13</td> </tr> <tr> <td>valid to</td> <td></td> </tr> </table> </td> <td> </td> <td> <table border="1" cellpadding="2" cellspacing="0"> <th colspan="2">Course identifiers</th> <tr> <td>Long name</td> <td>%FORMFIELD{"Bezeichnung"}%</td> </tr> <tr> <td>CID</td> <td>F07_IBA</td> </tr> <tr> <td>CEID (exam identifier)</td> <td></td> </tr> </table> </td> </tr> </table> </sticky><sticky> <table border="0"> <tr valign="top"> <td> <table border="1" cellpadding="2" cellspacing="0"> <th colspan="2">Contact hours per week (SWS)</th> <tr> <td>Lecture</td> <td>%FORMFIELD{"VorlesungSWS"}%</td> </tr> <tr> <td>Exercise (unsplit)</td> <td>%FORMFIELD{"UebungGanzSWS"}%</td> </tr> <tr> <td>Exercise (split)</td> <td>%FORMFIELD{"UebungHalbSWS"}%</td> </tr> <tr> <td>Lab</td> <td>%FORMFIELD{"PraktikumSWS"}%</td> </tr> <tr> <td>Project</td> <td>%FORMFIELD{"ProjektSWS"}%</td> </tr> <tr> <td>Seminar</td> <td>%FORMFIELD{"SeminarSWS"}%</td> </tr> <tr> <td>Tutorial(voluntary)</td> <td>%FORMFIELD{"TutoriumSWS"}%</td> </tr> </table> </td> <td> </td> <td> <table border="1" cellpadding="2" cellspacing="0"> <th colspan="2">Total contact hours</th> <tr> <td>Lecture</td> <td>%FORMFIELD{"VorlesungPZ"}%</td> </tr> <tr> <td>Exercise (unsplit)</td> <td>%FORMFIELD{"UebungGanzPZ"}%</td> </tr> <tr> <td>Exercise (split)</td> <td>%FORMFIELD{"UebungHalbPZ"}%</td> </tr> <tr> <td>Lab</td> <td>%FORMFIELD{"PraktikumPZ"}%</td> </tr> <tr> <td>Project</td> <td>%FORMFIELD{"ProjektPZ"}%</td> </tr> <tr> <td>Seminar</td> <td>%FORMFIELD{"SeminarPZ"}%</td> </tr> <tr> <td>Tutorial (voluntary)</td> <td>%FORMFIELD{"TutoriumPZ"}%</td> </tr> </table> </td> <td> </td> <td> <table border="1" cellpadding="2" cellspacing="0"> <th colspan="2">Max. capacity</th> <tr> <td>Exercise (unsplit)</td> <td>%FORMFIELD{"UebungGanzTeilnehmer"}%</td> </tr> <tr> <td>Exercise (split)</td> <td>%FORMFIELD{"UebungHalbTeilnehmer"}%</td> </tr> <tr> <td>Lab</td> <td>%FORMFIELD{"PraktikumTeilnehmer"}%</td> </tr> <tr> <td>Project</td> <td>%FORMFIELD{"ProjektTeilnehmer"}%</td> </tr> <tr> <td>Seminar</td> <td>%FORMFIELD{"SeminarTeilnehmer"}%</td> </tr> </table> </td> </tr> </table> </sticky> *Total effort (hours):* %FORMFIELD{"Gesamtaufwand"}% ---++++ Instruction language * German ---++++ Study Level * %FORMFIELD{"Niveau"}% ---++++ Prerequisites * basic skills in signal processing * basic skills in Java and/or C * basic skills in analysis and linear algebra ---++++ Textbooks, Recommended Reading * Rafael C. Gonzalez, Richard E. Woods, Digital Image Processing, Prentice Hall * Scott E Umbaugh, COMPUTER VISION and IMAGE PROCESSING: A Practical Approach Using CVIPtools, Prentice Hall * Wolfgang Abmayer, Einführung in die digitale Bildverarbeitung,Teubner ---++++ Instructors * Prof. Dr. Thieling ---++++ Supporting Scientific Staff * Dipl.-Ing. Peter Pohlig ---++++ Transcipt Entry Industrial Computer Vision ---+++ Assessment <sticky> <table border="1" cellpadding="2" cellspacing="0"> <th colspan="2">Type</th> <tr> <td>oE</td> <td>normal case (except on large numbers of assessments: wE</td> </tr> </table> </sticky> <sticky> <table border="1" cellpadding="2" cellspacing="0"> <th colspan="2">Total effort [hours]</th> <tr> <td>oE</td> <td>10</td> </tr> </table> </sticky> *Frequency:* 3/Jahr ----- ---++ Course components %STARTSECTION{"Vorlesung / Übung"}% ---+++ <u>Lecture/Exercise</u> ---++++ Objectives ---+++++ Lerninhalte (Kenntnisse) * image construction and access to image data * grey-level image and colour image * development environment * software design tools * compiler * linker * debugger * softwaretools for image processing and image analysis * softare-based access to image data and parameters * overview of the available ip-modules (moduls dor image processing and image analysis) * design and implementation of own ip-moduls * design of algorithmic chains based on ip-modules using visual programming * segmentation * histogram-based segmentation * histogram analysis * shading and its compensation * region-based segmentation * filling * split and merge * region growing * contour-based segmentation * contour tracking * hough-transformation * feature extraction * geometric features * basic features (area, perimeter, shape factor) * central moments * normalized central moments * polar distance * curvature * DFT of polar distance and curvature * color features (HSI) * texture features * co-occurrence matrix * haralick features * Klassifikation von Merkmalen * terms and concepts * feature vector, feature space, object classes * supervised / unsupervised classification * learning / not learning classification * typical methods * quader method * minimum distance * nearest neighbour * maximum likelihood * neuronale Netze * the artificial neuron as a simple classifier * operation * activation function * bias * training a neuron (gradient descent) * multi-layer-perceptron * operation * purposes of the layers * backpropagation training algorithm * development environment for creating and training neural networks * design and configuration of neural networks * training neural networks * verification tof rained networks * generating C-functions from trained networks ---+++++ Aquired Skills * the presented methods for segmentation can be * named * described * delineated in terms of application areas * evaluated in terms of advantages and disadvanteges * problemspecific parameterized * the presented methods for feature extraction can be * named * described * delineated in terms of application areas * evaluated in terms of advantages and disadvanteges * problemspecific parameterized * the presented methods for scallsification can be * named * described * delineated in terms of application areas * evaluated in terms of advantages and disadvanteges * problemspecific parameterized ---++++ Additional Component Assessment * none %ENDSECTION{"Vorlesung / Übung"}% %STARTSECTION{"Praktikum"}% ---+++ <u>Lab</u> ---++++ Objectives ---+++++ Aquired Skills * purposeful handling of the software development environment * purposeful handling of the softwaretools for image processing and image analysis * purposeful handling of the development environment for creating and training neural networks ---+++++ Operational Competences * deal with complex tasks in a small team * derive complex solutions that can be implemented using image processing and image analysis ---++++ Additional Component Assessment * none %ENDSECTION{"Praktikum"}% %ENDSECTION{"no_toc"}%
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