EECS 490

References

Digital Image Processing USING MATLAB®

Rafael C. Gonzalez, Richard E. Woods and Steven L. Eddins, Prentice-Hall, 2004. This is a specialized version of our textbook with very comprehensive and detailed explanations of MATLAB implementation of image processing algorithms.

• Preface Author's Preface, Table of Contents, About the Authors(pdf, 724 kB)
• Chapter 1 Introduction (pdf, 3 MB)
• Chapter 2 Fundamentals (pdf, 3.3 MB)
• Chapter 3 Intensity Transformations and Spatial Filtering (pdf, 3.2 MB)
• Chapter 4 Frequency Domain Processing (pdf, 3.1 MB)
• Chapter 5 Image Reconstruction (pdf, 8.7 MB)
• Chapter 6 Color Image Processing (pdf, 5.8 MB)
• Chapter 7 Wavelets (pdf, 4.9 MB)
• Chapter 9 Morphological Image Processing (pdf, 4.84 MB)
• Chapter 10 Image Segmentation (pdf, 5.12 MB)
• Chapter 11 Representation and Description (pdf, 8 MB)
• Chapter 12 Object Recognition (pdf, 3.08 MB)
• Appendix A MATLAB Function Summary (pdf, 1.1 MB)
• Appendix B Interactive Color Editor (pdf, 2.52 MB)
• Appendix C MATLAB M-Functions (pdf, 2.5 MB)
• Bibliography (pdf, 385 kB)
• Index (pdf, 1.28 MB)

Computer Vision

Linda Shapiro and George Stockman, Prentice-Hall, 2001. This appears to be a very good computer vision textbook.

• Chapter 9 Motion from 2D Image Sequences (pdf, 3.3 MB)
• Chapter 11 Matching in 2D(pdf, 4.1 MB)
• Chapter 13 3D Sensing and Image Registration(pdf, 5.9 MB)
• Bibliography (pdf, 385 kB)
• Index (pdf, 1.28 MB)

Computer Vision: A Modern Approach

David Forsyth and Jean Ponce, Prentice-Hall, 2004. This is a new textbook which looks at computer vision - the construction of models which can be used to describe and reason about the world from a computer framework. Some reviewers think this is a terrible textbook.

• Chapter 1 Cameras (pdf, 2 MB)
• Chapter 2 Geometric Camera Models (pdf, 1.6 MB)
• Chapter 3 Geometric Camera Calibration (pdf, 1.6 MB)
• Chapter 10 The Geometry of Multiple Views (pdf, 1.8 MB)
• Chapter 11 Stereopsis (pdf, 2.3 MB)
• Chapter 12 Affine Structure from Motion (pdf, 2.4 MB)
• Chapter 13 Projective Structure from Motion (pdf, 2.5 MB)
• Chapter 17 Tracking with Linear Dynamic Models (pdf, 2.4 MB)

Castleman: Digital Image Processing

Kenneth R. Castleman, Prentice-Hall, 1995, ISBN 0-13-211467-4. Well written textbook which has more of an emphasis on linear systems than our textbook.

• Chapter 8 Geometric operations, spatial and gray level transformations. (pdf, 5.2 MB)
• Chapter 13 Digital image transformations: the DFT, DCT, DST, continuous sine, Walsh, slant, Haar, Karhunen-Loeve, and other transforms. (pdf, 1.9 MB)
• Chapter 14 Wavelet transformations, the continuous wavelet transform, wavelet expansions, the discrete wavelet transform, subband and multi-band resolution (pdf, 4.2 MB)

Mix: Random Signal Processing

Dwight F. Mix, Prentice-Hall, 1995, ISBN 0-02-381852-2. Easy to understand book which derives, among other things, the Kalman filter which is used for estimation in vision.

• Chapter 5.2 A review of time correlation functions. (pdf, 890 kB)
• Chapter 8 Optimim filters: derivation of the Weiner and Kalman filters. (pdf, 3.1 MB)

Kalman filters

A collection of references which may be useful.

• Two excellent Lectures by Mills at the University of Nottingham on the fundamentals of the Kalman filter (pdf, 84 kB)and a specific example to the tracking of trucks in images . (pdf, 104 kB)
• Greg Welch and Gary Bishop maintain a useful site on the Kalman filter which includes an introduction, some tutorials, and some background on Kalman (including his original paper).

Haralick and Shapiro: Computer and Robot Vision, Volume I

Robert M. Haralick and Linda G. Shapiro, Addison-Wesley, 1992, ISBN 0-201-10877-1. Robert Haralick is one on the most prolific authors in the image processing/computer vision research area. This is the first volume of a very comprehensive two-volume set on computer vision and its applications. This book is now very hard to find. Linda Shapiro has also written a newer computer vision textbook.

• Chapter 2 Binary machine vision: thresholding, optimum thresholding, connected component labeling, segmentation and signature analysis. (pdf, 1.8 MB)
• Chapter 3 Binary machine vision: region properties, extreme points, spatial moments, signature properties. (pdf, 3.7 MB)

Computer Vision

Dana H. Ballard and Christopher M. Brown, Prentice-Hall, 1982, ISBN 0-165316-4. This is a relatively old book but it has some good chapters on image acquisition and the mathematics of image processing although the descriptions of the technology are rather dated.

• Chapter 2 Image formation: how images are formed, reflectance, Fourier transforms, color, imaging devices such as cameras and scanners, and just a mention of projection reconstruction. (pdf, 4.81 MB)
• Appendix A1 Coordinate systens, homegeneous coordinates, trigonometry, analytical geometry, homogeneous coordinate transformations, camera calibration, lreast squares curve fitting, the pseudoinverse, interpolation, the FFT and finding roots of polynomials. This is in general one of the most useful mathematical appendices I have ever come across. The matrix pseudoinverse is something which you will repeatedly use. (pdf, 1.83 MB)

Introduction to Fourier Optics

Joseph W. Goodman, McGraw-Hill, 1968, ISBN 07-023776-X. This is the oldest book in this set of references and has an intimidating title which does not seem relevant to image processing. However, it has an excellent explanation of two dimensional Fourier transforms and their properties.

• Chapter 2 This is an excellent presentation of the mathematics of two-dimensional signal processing. It covers basic definitions, mathematical properties of the two-dimensional Fourier transform, the Fourier-Bessel transform for radially symmetric systems, two-dimensional sampling theorem, and properties of the Dirac delta function. (pdf, 2.15 MB)

Robotics: Control, Sensing, Vision, and Intelligence

K.S. Fu, R.C. Gonzalez, and C.S.G Lee, McGraw-Hill, 1987, ISBN 0-07-022625-3. This is an excellent robotics textbook which includes what amounts to a complete mini-course on image processing and computer vision written by R.C. Gonzalez, the author of our current image processing textbook. Since the author is the same, the notation is similar and much easier to follow than that of most other robotics textbooks which include vision and image processing.

• Chapter 6 Sensing: optical range sensing, proximity sensing, and a large section on tactile, force and torque sensors for robots, . (pdf, 2.4 MB)
• Chapter 7 Low-level vision: optical sensors, camera models, camera geometry in homogeneous coordinates, intensity transformations, thresholding, basic spatial domain image processing techniques such as edge operators and gradients. (pdf, 7.5 MB)
• Chapter 8 High-level vision: Image segmentation, optimum thresholding, region and edge based segmentation, split-merge techniques, feature extraction including boundary and region descriptors, three-dimensional image segmentation, pattern recognition and scene interpretation. (pdf, 7.9 MB)

Industrial Robotics: Computer Interfacing and Control

Wesley E. Snyder, Prentice-Hall, 1985, ISBN 0-13-463159-5. This is an older book which has some good chapters on motors, sensors, and image processing.

• Chapter 4 Actuators: DC Motors, Stepping Motors, and Actuators. Hydraulic and pneumatic actuators. (pdf, 1.3 MB)
• Chapter 12 Sensors: touch, proximity, and ultrasonic sensors are emphasized in this chapter. (pdf, 981 kB)
• Chapter 13 Image sensors, images, sampling and quantization, image processing functions, image acquisition systems, thresholding, region growing, blob descriptors, shape recognition, illumination (pdf, 2.1 MB)

Image Deskewing

Some selected journal and conference papers to help you get started on the document image processing project.

• Automatic Text Skew Estimation in Documents by Su Chen, Robert M. Haralick, and Ihshin Phillips, in Document Analysis and Recognition, 1995., Proceedings of the Third International Conference on , Volume: 2 , 14-16 Aug. 1995. Pages:1153 - 1156 vol.2 (pdf, 376 kB)
• Skew and Slant Correction for Document Images Using Gradient Direction by Changming Sun and Deyi Si, in Document Analysis and Recognition, 1997., Proceedings of the Fourth International Conference on , Volume: 1 , 18-20 Aug. 1997. Pages:142 - 146 vol.1 (pdf, 668 kB)
• An Enhanced Skew Angle Estimation Technique for Binary Document Images by Huiye Ma and Zhenwei Yu, in Document Analysis and Recognition, 1999. ICDAR '99. Proceedings of the Fifth International Conference on , 20-22 Sept. 1999. Pages:165 - 168. (pdf, 40 kB)
• Document Skew Detection Using Minimum-Area Bounding Rectangle by Reza Safabakhsh and Shahram Khadivi, in Information Technology: Coding and Computing, 2000. Proceedings. International Conference on , 27-29 March 2000. Pages:253 - 258. (pdf, 288 kB)
• A Fast Multifunctional Approach for Document Image Analysis by Abhishek Gattani, Maitrayee Mukerji and Hareish Gur, in Document Analysis and Recognition, 2003. Proceedings. Seventh International Conference on , 3-6 Aug. 2003. Pages:1178 - 1182. (pdf, 260 kB)

Face Recognition

Some selected journal and conference papers to help you get started on the face recognition project.

• Computer operation via face orientation by P. Ballard and G.C. Stockman; Pattern Recognition, 1992 . Vol.1. Proceedings 11th IAPR International Conference on Computer Vision and Applications, 30 Aug.-3 Sept. 1992 Pages:407 - 410 (pdf, 393 kB)
• Detecting faces in images: a survey by Ming-Hsuan Yang; D.J. Kriegman, and N. Ahuja; IEEE Transactions on Pattern Analysis and Machine Intelligence,Volume: 24 , Issue: 1 , Jan. 2002. Pages:34 - 58 (pdf, 1.26 MB)
• Low-dimensional procedure for the characterization of human faces by L.Sirovich and M. Kirby, in J. Optical Society of America, Vol. 4, No. 3, Page 519-524, March 1987. (pdf, 4.37 MB)

Chocolate Chips

Some selected journal and conference papers to help you get started on the chip counting project.

• Fuzzy Models to Predict Consumer Ratings for Biscuits Based on Digital Image Features by Valerie J. Davidson, Joanne Ryks, and Terrence Chu; IEEE Transactions on Fuzzy Systems, Vol. 9, No. 1, February 2001, Pages:62 - 67 (pdf, 111 kB)

Misc. References

Selected journal and conference papers.

• Machine Perception of Three Dimensional Solids by L.G. Roberts, in Computer Methods in Image Analysis, Edited by J.K. Aggarwal, Richard O. Duda, and Azriel Rosenfeld, IEEE Press. (pdf, 2.6 MB)
• CyberWarfare: Steganography vs. Steganalysis by Huaiqing and Shuozhong Wang, in Communications of the ACM, Vol. 47, No.10, Pages 76-82, October 2004. (pdf, 316 kB)

Visual Object Recognition and Tracking System (VORTS)

This vision tracking system was implemented by Kevin Briggman (senior project) and Tom Lorimor (MS project in CE). The goal of this project was to develop a computationally simple algorithm for a mobile robot that could track and follow another robot (called the drone). This system was implemented using the EECS 375 68HC11 platform for both robots, a Connectix low resolution color camera with a serial interface, and a 386 single board computer with RAM disk for image processing.

• Final Report (pdf, 263 kB)
• Project Presentation (ppt, 252 kB)