Majitar, India. Abstract—Data compression coupled with the availability of high bandwidth networks and storage capacity have created the overwhelming production of multimedia content, this paper briefly describes techniques for content-based analysis, retrieval and filtering of News Videos and focuses on basic methods for extracting features and information that will enable indexing and search of any news video based on its content and semantics. The major themes covered by the study include
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COMPRESSION USING MATLAB 7.10.0 3.1.1 Workflow We successfully compressed a black & white photograph (source: Dresden Image Database) implementing JPEG algorithm in Matlab and compressed the images to 1/4th of the original image size. This was achieved by dividing the image in blocks of 8×8 pixels and applying a discrete cosine transform (DCT) on each partition of the images. The resulting coefficients were quantized and less significant coefficients are set to zero. In order to omit redundancy
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Digital Image Processing Second Edition Rafael C. Gonzalez University of Tennessee Richard E. Woods MedData Interactive Prentice Hall Upper Saddle River, New Jersey 07458 Library of Congress Cataloging-in-Pubblication Data Gonzalez, Rafael C. Digital Image Processing / Richard E. Woods p. cm. Includes bibliographical references ISBN 0-201-18075-8 1. Digital Imaging. 2. Digital Techniques. I. Title. TA1632.G66 621.3—dc21 2001 2001035846 CIP Vice-President and Editorial Director, ECS: Marcia
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information obtained during UC is not discarded, but is used as an initial step toward subsequent SC. Thus, the power of both image analysis strategies can be combined in an integrative computational procedure. This is achieved by applying “Hyper-BF network”. Here we worked a different procedures for the training, preprocessing and vector quantization in the application to medical image segmentation and also present the segmentation results for multispectral 3D MRI data sets of the human brain with respect
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which requires most of the computation, it allows our mobile platform to detect traffic signs and differentiate between them. Once the parameters are available, we can computationally cheap detect our classified objects. The result of our very fast image processing allows us to integrate the method
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Computer Vision Class test questions CT# 1 1. Define: Digital Image, Computer Vision Application, Human Vision Application, Image Analysis, Digital image processing, Computer imaging, Nyquist criterion, Vector image, Raster image, Color Model, Pixel. 2. Why is computer vision difficult? 3(a). Describe the four basic types of digital images. (b) Consider a 512*512 color image. Calculate the number of bytes used in this image where each pixel is associated with 3 bytes of color information
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Jurnal Teknologi Full Paper TRAFFIC SIGN DETECTION AND RECOGNITION: REVIEW AND ANALYSIS Nursabillilah Mohd Ali*, Mohd Safirin Karis, Amar Faiz Zainal Abidin, Bahzifadhli Bakri, Ezreen Farina Shair, Nur Rafiqah Abdul Razif Faculty of Electrical Engineering, Universiti Teknikal Malaysia Melaka, Malaysia Graphical abstract Article history Received 15 May 2015 Received in revised form 1 July 2015 Accepted 11 August 2015 *Corresponding author nursabillilah@utem.edu Abstract Over the years, traffic
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differences. Background subtraction differentiating foreground objects from the stationary parts of the scene is one of the modules of annotation. Valuable low level cue information is obtained by the module for performing high-level tasks of motion analysis, like motion estimation, tracking, etc. In recent research, 3D scene reconstruction and geometric model matching are the basis of perception where a 3D sample point cloud are used to match with the trained features. A semantic perception method
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Digital Image Processing: PIKS Inside, Third Edition. William K. Pratt Copyright © 2001 John Wiley & Sons, Inc. ISBNs: 0-471-37407-5 (Hardback); 0-471-22132-5 (Electronic) DIGITAL IMAGE PROCESSING DIGITAL IMAGE PROCESSING PIKS Inside Third Edition WILLIAM K. PRATT PixelSoft, Inc. Los Altos, California A Wiley-Interscience Publication JOHN WILEY & SONS, INC. New York • Chichester • Weinheim • Brisbane • Singapore • Toronto Designations used by companies to distinguish their products
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Student Attendance System Based On Fingerprint Recognition and One-to-Many Matching A thesis submitted in partial fulfillment of the requirements for the degree of Bachelor of Technology in Computer Science and Engineering by Rishabh Mishra (Roll no. 107cs016) and Prashant Trivedi (Roll no. 107cs015) Under the guidance of : Prof. B. Majhi Department of Computer Science and Engineering National Institute of Technology Rourkela Rourkela-769 008, Orissa, India 2 . Dedicated
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