ECGR6118 Applied Digital Image Processing Fall 2008 Prof. Weldon: 222B Woodward, email@example.com See home website for office hours: wws2.uncc.edu/tpw/ Course Web site: http://wws2.uncc.edu/courses/eegr6118/ Textbooks: Required: "Digital Image Processing: PIKS Scientific Inside," 4th Ed. by William K. Pratt, Wiley-Interscience, 2008, ISBN: 0471767778. Optional: Teach Yourself C++, 4th Ed., A. Stevens, MIS Press, 1995. Optional: "The Java Tutorial, 3rd Ed., A Short Course on the Basics," M. Campione, K. Walrath, A. Huml, Addison Wesley, 2001. Optional: "Fundamentals of Digital Image Processing," Anil K. Jain, Prentice Hall, 1989. Grading will be based on projects/quizzes/assignments (60%) and Final Project (40%). Grading scale: 90-100 A, 80-89 B, 70-79 C, with ``curve,'' if any, entirely at the discretion of the instructor. Quizzes may be given without warning. Collaboration (not copying!) on homework and computer projects is encouraged. However, students may NOT share program code or report material. Class attendance and participation are expected, and the instructor reserves the right to reduce the grade on any work, or the course, for poor attendance. You must read the textbook; it is impossible to cover all material during class. The course will roughly follow the outline below; key topics are noted. Week/Chap. Topic 1/1-6 Image Fundamentals Vision, images, color, coordinates, matrix forms 2/7-8 Convolution and transforms Convolution, Fourier transform, Cosine transform, Hadamard, Project 1: Transforms 3-4/- Sub-band coding and pyramid/wavelet representations Filtering, QMF, subband, pyramid, wavelet, compression Project 2: Pyramids, sub-bands, compression 5/9-12 Image enhancement: Spatial, frequency domain, histogram eq., local methods, subtraction, filtering Project 3: Enhancement 6/14 Morphology: Dilation, erosion, open, close, gray-scale, skeleton Project 4: Morphology 7/15 Edge Detection: Edges, gradient, laplacian, Hough transform Project 5: Edges 8-9/16 Feature Extraction B-distance, error, amplitude features, texture, Gabor filter Project 6: Texture features 9-10/17 Segmentation Thresholding, region growing, split/merge, clustering Project 7: Segmentation 11/- 3D Images and Image Volumes Project 8 3D 12 Final Project proposals due 12-14/8 Final projects 15 Final project presentations Final reports due: During scheduled final exam period (see published schedules) Presentation make-up: During scheduled final exam period We cannot devote much time in class to programming. If you are not familiar with C++ or Java or Mathcad, you must become proficient early in the semester. Use my office hours to address any questions that you may have on C++ or java or Mathcad: DO NOT PUT THIS OFF!! If you miss an exam/quiz for any reason, you will receive a grade of zero (exceptional circumstances must be documented and/or approved by the instructor at least 24 hours prior to the exam). Exams may be open book, NO calculators. Late homeworks/projects will not be accepted. Frequent absence from class or disruptive behavior will result in a severe grade reduction. Late projects will not be accepted, or may be penalized up to 20 percent per day, solely at the instructor's discretion. Poor or late project proposals will adversely affect project grade. Absence from each project session will result in 20% grade reduction, beyond 1 absence. Absence from final project sessions will each result in 20% reduction in final project grade, beyond 1 absence. It is the responsibility of the student to be familiar with the academic regulations, degree requirements, and course requirements as outlined in the current University Catalog. The official university guidelines supersede any contradictions that may exist in this handout. PREREQUISITES: ALL STUDENTS MUST MEET PREREQUISITES AND COREQUISITES FOR THIS COURSE as published in the UNCC Catalog. Prerequisite: Corequisite: Prerequisite or corequisite: You should be familiar with Fourier transforms and filtering concepts. Look over the textbook during the first week of class to determine if you have sufficient background for this course. ACADEMIC INTEGRITY: Students have the responsibility to know and observe the requirements of The UNCC Code of Student Academic Integrity . This code forbids cheating, fabrication or falsification of information, multiple submission of academic work, plagiarism, abuse of academic materials, and complicity in academic dishonesty. Grades in this course will be adversely affected by academic dishonesty, for example zero credit for work involving dishonesty and/or course grade reduced to F.