EECS 490: Fall 2004

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)

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)

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)

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 actuatos. (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 fucntions, 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 Rectange 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)