Dig Image Anal

Instructors

• Ying Wu

Meeting Info

• Technological Institute M152 - TuTh 11:00AM - 12:20PM

Overview of class

• CATALOG DESCRIPTION: Introduction to computer and biological vision systems, image formation, edge detection, image segmentation, texture, representation and analysis of two-dimensional geometric structures, and representation and analysis of three-dimensional structures.
  
  DETAILED COURSE TOPICS :
  
  1.Introduction to image formation (1 week)
  2.Binary image processing (2 weeks)
  3.Color and color segmentation (1 week)
  4.Region segmentation (1 week)
  5.Edge, contour, Hough transform and texture (2 weeks)
  6.Motion and tracking (1 week)
  7.3D geometry, calibration, pose and stereo (1 week)
  8.Lighting and applications (1 week)
  MACHINE PROBLEMS:
  
  1.Implementation of connect component analysis
  2.Implementation of morphological operators
  3.Implementation of histogram equalization and lighting compensation
  4.Implementation of color segmentation
  5.Implementation of canny edge detector
  6.Implementation of Hough transform.
  7.Implementation of camera calibration
  8.Implementation of 3D pose determination
  
  FINAL PROJECTS:
  
  Based on the machine problems, the course involves a final project to design a vision-based interface system, i.e., a "virtual gun," where the cursor moves with your fingertips. The idea is to locate and track a fingertip through a video sequence accurately and robustly. The project consists of three parts: (1) a working demo, (2) a 15-minute presentation, and (3) a 15-page report.

Registration Requirements

• PREREQUISITES : EECS 230
  
  PREREQUISITES BY TOPIC :
  
  Linear algebra
  
  Probability
  
  Computer programming in C

Learning Objectives

• COURSE GOALS: The goal of this course is to provide students with a basic understanding of the fundamentals and applications of digital image analysis (or computer vision) techniques including 2-D and 3-D paradigms to solve real world applications.
  
  COURSE OBJECTIVES: When a student completes this course, s/he should be able to:
  
  1.Understand the projection geometry in the image formation process.
  2.Design and implement computer programs to perform image feature extraction.
  3.Design and implement computer programs for image segmentation.
  4.Design and implement computer programs for motion analysis and tracking.
  5.Understand the basic techniques and issues in 3-D computer vision.
  6.Design and build a real vision-based interaction system.

Evaluation Method

• GRADES:
  
  Machine problems - 50%
  
  Final project - 50%

Class Materials (Required)

• REQUIRED TEXT: None
  
  READINGS : Papers from journals, conference proceedings, or book chapters will be assigned.

Class Materials (Suggested)

• REFERENCE TEXT: R. Jain, R. Kasturi, and B. G. Schunck, Machine Vision , McGraw-Hill, Inc. 1995.

Class Notes

• ABET CONTENT CATEGORY: 100% Engineering (Design component).

Class Attributes

• Prerequisites apply, see description
  
  

Enrollment Requirements

• 
  Add Consent: Department Consent Required
  

Current as of 05/03/13 12:45:16 PM

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