Image Processing and Pattern Recognition: Fundamentals and Applications
Lecturer:
Prof. Frank Y. Shih (New Jersey Institute of Technology)
Place:
National Institute of Informatics, 12F, conference room (1208, 1210)
Date:
June 16-20, 24 2pm - 4:30pm
Abstract:
Images are used for a variety of purposes, including entertainment, medical, business, industrial, military, civil, security, and scientific. The interests in digital image processing stem from the improvement of pictorial information for human interpretation and the processing of scene data for autonomous machine perception. Many new practical image processing, watermarking, and pattern recognition techniques will be introduced in this lecture series to illustrate the framework that provides assistance and tools in understanding and implementing the fundamental principles. The topics include image fundamentals and enhancement, mathematical morphology, image segmentation and representation, feature extraction, pattern recognition, image watermarking and steganography, face recognition, document processing, and solar image analysis.
Short Bio of the Lecturer:
Professor Frank Shih received Ph.D. from Purdue University. He is presently a full professor in CS Department, New Jersey Institute of Technology, USA. He is the Director of Computer Vision Laboratory. He held a visiting professor position at Princeton University, Columbia University, and National Taiwan University. He is an internationally well-known scholar and serves on the Editorial Board of the International Journal of Pattern Recognition, the International Journal of Pattern Recognition Letters, the International Journal of Pattern Recognition and Artificial Intelligence, the International Journal of Recent Patents on Engineering, the International Journal of Recent Patents on Computer Science, the International Journal of Internet Protocol Technology, and the Journal of Internet Technology. He served as a steering member, committee member, and session chair for numerous professional conferences and workshops. He has received numerous grants from the National Science Foundation, Navy and Air Force, and Industry. He authored a book on Digital Watermarking and Steganography, and is writing two books on Image Processing and Pattern Recognition. He has published eight book chapters and over 190 technical papers. His current research interests include image processing, computer vision, watermarking and steganography, sensor networks, pattern recognition, bioinformatics, information security, robotics, fuzzy logic, and neural networks.
Lecture 1
Image Fundamentals and Enhancement
16th June 2008, 2pm-4:30pm
In this lecture, I will introduce image fundamentals and mathematical preliminaries that are often used in image processing, including Laplace transform, Fourier transform, z-transform, cosine transform, and wavelet transform. I will also introduce the commonly used image enhancement techniques, including gray scale transformation, piecewise linear transformation, bit plane slicing, histogram equalization, histogram specification, enhancement by arithmetic operations, smoothing filter, sharpening filter, image blur types, and quality measures.
Lecture 2
Mathematical Morphology
17th June 2008, 2pm-4:30pm
Mathematical morphology can extract image shape features, such as edges, fillets, holes, corners, wedges, and cracks, by operating with various shaped structuring elements. In industrial vision applications, mathematical morphology can be used to implement fast object recognition, image enhancement, segmentation, and defect inspection. In this lecture, I will introduce binary morphology, opening and closing, hit-or-miss transform, grayscale morphology, morphological edge operator, alternating sequential filters, recursive morphological operation, soft morphological operation, and general sweep morphological operation.
Lecture 3
Image Segmentation and Representation
18th June 2008, 2pm-4:30pm
In this lecture, I will introduce a number of image segmentation techniques. They include thresholding, component labeling, locating object contours by the snake model, edge detection, linking edges by adaptive mathematical morphology, automatic seeded region growing, and top-down region dividing. I will also discuss different region representation schemes, such as run-length coding, binary tree and quadtree, skeleton, and shape number, and different boundary representation schemes, such as chain code, crack code and midcrack code, fitting-line segments, and Fourier descriptors.
Lecture 4
Feature Extraction and Pattern Recognition
19th June 2008, 2pm-4:30pm
In this lecture, I will introduce the methods of feature extraction in image processing and analysis. They include Fourier descriptor and moment invariants, shape number, corner and circle detection, Hough transform, principal component analysis, linear discriminate analysis, and feature reduction. I will describe distance transformation and shortest path planning. I will also present different pattern recognition methods, including the unsupervised clustering algorithm, support vector machine, neural networks, the adaptive-resonance-theory (ART) network, fuzzy sets, and image analysis.
Lecture 5
Image Watermarking and Steganography
20th June 2008, 2pm-4:30pm
With the fast increasing volume of electronic commerce web sites and applications, intellectual property protection is an extremely important concern for content owners who exhibit digital representations of photographs, books, manuscripts, and original artwork on the Internet. Moreover, as available computing power continues to rise, there is an increasing interest in protecting video files from attack. The applications are widely spread on electronic publishing, advertisement, merchandise ordering and delivery, picture galleries, digital libraries, online newspapers and magazines, digital video and audio, personal communication, etc. In this lecture, I will introduce watermarking classification, spatial domain watermarking, frequency domain watermarking, fragile watermark, robust watermark, and combinational domain digital watermarking. I will also introduce types of steganography, applications of steganography, embedding security and imperceptibility, examples of steganography software, and genetic algorithm based steganography.
Lecture 6
Face, Document, and Solar Image Applications
24th June 2008, 2pm-4:30pm
In this lecture, I will introduce the application of image processing and pattern recognition on face images, including face and facial feature extraction using SVM, the extraction of head and face boundaries and facial features, the recognition of facial action units, and facial expression recognition. I will also introduce block segmentation and classification, rule-based character recognition subsystem, logo identification, fuzzy typographical analysis for character preclassification, and fuzzy model for character classification. I will present the applications of machine learning techniques to automated detection and classification of solar events.
