'Wavelet decomposition' presentation slideshows

Content-based Image Retrieval (CBIR)

Content-based Image Retrieval (CBIR). Searching a large database for images that match a query: What kinds of databases? What kinds of queries? What constitutes a match? How do we make such searches efficient?. Applications. Art Collections e.g. Fine Arts Museum of San Francisco

1.14k views • 71 slides

Detection, segmentation and classification of heart sounds

Detection, segmentation and classification of heart sounds. Daniel Gill Advanced Research Seminar May 2004. Automatic Cardiac Signals Analysis. Problems : Pre-processing and noise treatment. Detectionsegmentation problem. Classification problem:

520 views • 37 slides

Blind Steganography Detection Using a Computational Immune System Approach: A Proposal

Blind Steganography Detection Using a Computational Immune System Approach: A Proposal. Capt Jacob T. Jackson Gregg H. Gunsch, Ph.D Roger L. Claypoole, Jr., Ph.D Gary B. Lamont, Ph.D. Overview. Research goal Wavelet analysis background

654 views • 35 slides

REPRESENTATION of TSUNAMIS in GENERALIZED HYPERSPACE

REPRESENTATION of TSUNAMIS in GENERALIZED HYPERSPACE. Frank C. Lin* University of Maryland Eastern Shore, Princess Anne, MD. 21801, U.S.A . and Kingkarn Sookhanaphibarn** Ritsumeikan University,Kusatsu, Shiga,525-8577, Japan. Email: * linbfrank@gmail.com **kingkarn@ice.ci.ritsumei.ac.jp.

345 views • 34 slides

Introduction and Overview

Introduction and Overview. Dr Mohamed A. El-Gebeily Department of Mathematical Sciences KFUPM mgebeily@kfupm.edu.sa. Why Wavelets? Comparison With Fourier Analysis What is Wavelet Analysis? The Continuous Wavelet Transform The Discrete Wavelet Transform Introduction to Wavelet Families

462 views • 33 slides

Numerical simulation of internal tides in the Sicily and Messina Straits

443 views • 27 slides

Content Based Color Image Retrieval vi Wavelet Transformations

Information Retrieval Class Presentation. Content Based Color Image Retrieval vi Wavelet Transformations. May 2, 2012 Author: Mrs. Y.M. Latha Presenter: Mahbubur Rahman Advisor: Prof. Susan Gauch. Table of Contents. Introduction Target Environment Proposed CBIR Wavelet Transform

370 views • 26 slides

* This work was partially supported by KSEF grant KSEF-1653-RDE-011, and is currently supported by KCF grant COMMFUND-1

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Image Processing and Computer Vision

Image Processing and Computer Vision. Outline. Research in Image Processing and Computer Vision Finding Images Content-based Image Retrieval. Find Images With Similar Colors. Find Images with Similar Shape. Goal: Find Images with Similar Content. Spectrum of Content-Based Image Retrieval.

293 views • 17 slides

Context-based vision system for place and object recognition

Context-based vision system for place and object recognition. Torralba, Murphy, Freeman & Rubin (2003). Context is useful for object recognition. Local and global image representations. Local representation (L) Wavelet decomposition N = 24 (6 orientations, 4 scales) Global representation

201 views • 10 slides

LES of Turbulent Flows : Lecture 7 (ME EN 7960-003)

LES of Turbulent Flows : Lecture 7 (ME EN 7960-003). Prof. Rob Stoll Department of Mechanical Engineering University of Utah Fall 2014. Turbulence modeling (alternative strategies).

244 views • 8 slides

LES of Turbulent Flows : Lecture 11 (ME EN 7960-008)

LES of Turbulent Flows : Lecture 11 (ME EN 7960-008). Prof. Rob Stoll Department of Mechanical Engineering University of Utah Spring 2011. Filtering the compressible N-S equations. What happens when we apply a filter to the compressible N-S equations?

260 views • 8 slides

Introduction

Figure 1 : Dorsal fin image. Characteristic feature points are indicated in red. Figure 3 : Two real-world results of the registration process. In each set, the originally extracted outlines are pictured on the top. The automatically registered outlines are pictured on the bottom.

121 views • 1 slides