Digital Image Processing Third Edition
01 Mar 2009-Journal of Biomedical Optics (International Society for Optics and Photonics)-Vol. 14, Iss: 2, pp 029901
TL;DR: The Scientist & Engineer's Guide to Digital Signal (PDF) Digital Image Processing, 3rd Edition,Instructor's Digital Signal Processing Using MATLAB how to improve campaign quality in a digital-first
Abstract: Sound / Processing.orgwww.iciap2021.org – International Conference on Image ImageProcessingPlaceGitHub BhanuPrakashNani/Image_Processing: Image matlab?? ??????????? ?????? ??_?? ...Fundamentals of Computer Graphics, Third Edition (??)Artificial Intelligence: A Modern Approach, 3rd EditionIntroduction to Signal ProcessingDxO PureRaw review: Impressive noise and lens processing Digital Image Processing (3rd Edition): Gonzalez, Rafael C Newest Questions Signal Processing Stack ExchangeImage Enhancement an overview | ScienceDirect TopicsTripleHead2Go Digital Edition| Multi-Display Adapter Digital imaging WikipediaCOVID-19 regulatory changes | Pharmaceutical Society of Discrete-Time Signal Processing, 3rd Edition PearsonD igital Image Processing Using MATLAB, 3rd editionThe Philosophy of Digital Art (Stanford Encyclopedia of The Scientist and Engineer's Guide to Digital Signal Render Techniques / Processing.orgDigitalDiagnost Digital radiography solutions | Philips Matrices and Digital Images | Klein Project BlogTIFF tags Library of CongressXML Signature Syntax and Processing Version 1.1Digital Image Processing 4th Edition amazon.comThe Scientist & Engineer's Guide to Digital Signal (PDF) Digital Image Processing, 3rd Edition,Instructor's Digital Signal Processing Using MATLABHow to improve campaign quality in a digital-first
Citations
More filters
01 Jan 2004
TL;DR: Comprehensive and up-to-date, this book includes essential topics that either reflect practical significance or are of theoretical importance and describes numerous important application areas such as image based rendering and digital libraries.
Abstract: From the Publisher:
The accessible presentation of this book gives both a general view of the entire computer vision enterprise and also offers sufficient detail to be able to build useful applications. Users learn techniques that have proven to be useful by first-hand experience and a wide range of mathematical methods. A CD-ROM with every copy of the text contains source code for programming practice, color images, and illustrative movies. Comprehensive and up-to-date, this book includes essential topics that either reflect practical significance or are of theoretical importance. Topics are discussed in substantial and increasing depth. Application surveys describe numerous important application areas such as image based rendering and digital libraries. Many important algorithms broken down and illustrated in pseudo code. Appropriate for use by engineers as a comprehensive reference to the computer vision enterprise.
3,627 citations
01 Jan 2010
TL;DR: This short paper shows that unnormalized cross correlation can be efficiently normalized using precomputing integrals of the image and image over the search window.
Abstract: Although it is well known that cross correlation can be efficiently implemented in the transform domain, the normalized form of cross correlation preferred for feature matching applications does not have a simple frequency domain expression. Normalized cross correlation has been computed in the spatial domain for this reason. This short paper shows that unnormalized cross correlation can be efficiently normalized using precomputing integrals of the image and image over the search window.
1,198 citations
Cites background or methods from "Digital Image Processing Third Edit..."
...For this reason normalized cross-correlation has been computed in the spatial domain (e.g., [ 7 ], p. 585)....
[...]
...The correlation between two signals (cross correlation) is a standard approach to feature detection [6, 7 ] as well as a component of more sophisticated techniques (e.g....
[...]
...[16, 7 , 13] and recent papers such as [1, 19]....
[...]
Journal Article•
TL;DR: The proposed algorithm’s efficiency can successfully detect and classify the examined diseases with an accuracy of 94%.
Abstract: P lant diseases have turned into a dilemma as it can cause significant reduction in both quality and quantity of agricultural products. Automatic detection of plant diseases is an essential research topic as it may prove benefits in monitoring large fields of crops, and thus automatically detect the symptoms of diseases as soon as they appear on plant leaves. The proposed system is a software solution for automatic detection and classification of plant leaf diseases. The developed processing scheme consists of four main steps, first a color transformation structure for the input RGB image is created, then the green pixels are masked and removed using specific threshold value followed by segmentation process, the texture statistics are computed for the useful segments, finally the extracted features are passed through the classifier. The proposed algorithm’s efficiency can successfully detect and classify the examined diseases with an accuracy of 94%. Experimental results on a database of about 500 plant leaves confirm the robustness of the proposed approach. Keywords: HSI, c olor c o-occurrence m atrix, t exture, SVM, p lant leaf diseases
319 citations
01 Jan 2012
TL;DR: A review of most popular color models are given with the explanation of the components, color system, and transformation formula for each other, application areas and usages are also included in this work.
Abstract: Colors are important for human for communicating with the daily encountered objects as well as his species, these colors should be represented formally and numerically within a mathematical formula so it can be projected on device/ computer storage and applications, this mathematical representation is known as color model that can hold the color space, by the means of color’s primary components (Red, Green, and Blue) the computer can visualizes what the human does in hue and lightness. In this paper; a review of most popular color models are given with the explanation of the components, color system, and transformation formula for each other, application areas and usages are also included in this work with the classification of color models according to its dependence and independence on the hardware device used in specific application, a summary of the advantages and disadvantages of the color models are also demonstrated in this work.
296 citations
01 Nov 2012
TL;DR: A novel computer vision-based fall detection system for monitoring an elderly person in a home care application that can achieve a high fall detection rate and a very low false detection rate in a simulated home environment is proposed.
Abstract: We propose a novel computer vision-based fall detection system for monitoring an elderly person in a home care application. Background subtraction is applied to extract the foreground human body and the result is improved by using certain postprocessing. Information from ellipse fitting and a projection histogram along the axes of the ellipse is used as the features for distinguishing different postures of the human. These features are then fed into a directed acyclic graph support vector machine for posture classification, the result of which is then combined with derived floor information to detect a fall. From a dataset of 15 people, we show that our fall detection system can achieve a high fall detection rate (97.08%) and a very low false detection rate (0.8%) in a simulated home environment.
294 citations
References
More filters
Book•
11 Feb 1984
TL;DR: This invaluable reference helps readers assess and simplify problems and their essential requirements and complexities, giving them all the necessary data and methodology to master current theoretical developments and applications, as well as create new ones.
Abstract: Image Processing and Mathematical Morphology-Frank Y. Shih 2009-03-23 In the development of digital multimedia, the importance and impact of image processing and mathematical morphology are well documented in areas ranging from automated vision detection and inspection to object recognition, image analysis and pattern recognition. Those working in these ever-evolving fields require a solid grasp of basic fundamentals, theory, and related applications—and few books can provide the unique tools for learning contained in this text. Image Processing and Mathematical Morphology: Fundamentals and Applications is a comprehensive, wide-ranging overview of morphological mechanisms and techniques and their relation to image processing. More than merely a tutorial on vital technical information, the book places this knowledge into a theoretical framework. This helps readers analyze key principles and architectures and then use the author’s novel ideas on implementation of advanced algorithms to formulate a practical and detailed plan to develop and foster their own ideas. The book: Presents the history and state-of-the-art techniques related to image morphological processing, with numerous practical examples Gives readers a clear tutorial on complex technology and other tools that rely on their intuition for a clear understanding of the subject Includes an updated bibliography and useful graphs and illustrations Examines several new algorithms in great detail so that readers can adapt them to derive their own solution approaches This invaluable reference helps readers assess and simplify problems and their essential requirements and complexities, giving them all the necessary data and methodology to master current theoretical developments and applications, as well as create new ones.
9,566 citations
Book•
22 Dec 2012
TL;DR: This self-contained volume will be valuable to all engineers, scientists, and practitioners interested in the analysis and processing of digital images.
Abstract: From the Publisher:
The purpose of this book is to provide readers with an in-depth presentation of the principles and applications of morphological image analysis. This is achieved through a step by step process starting from the basic morphological operators and extending to the most recent advances which have proven their practical usefulness. This self-contained volume will be valuable to all engineers, scientists, and practitioners interested in the analysis and processing of digital images.
4,018 citations
01 Jan 2004
TL;DR: Comprehensive and up-to-date, this book includes essential topics that either reflect practical significance or are of theoretical importance and describes numerous important application areas such as image based rendering and digital libraries.
Abstract: From the Publisher:
The accessible presentation of this book gives both a general view of the entire computer vision enterprise and also offers sufficient detail to be able to build useful applications. Users learn techniques that have proven to be useful by first-hand experience and a wide range of mathematical methods. A CD-ROM with every copy of the text contains source code for programming practice, color images, and illustrative movies. Comprehensive and up-to-date, this book includes essential topics that either reflect practical significance or are of theoretical importance. Topics are discussed in substantial and increasing depth. Application surveys describe numerous important application areas such as image based rendering and digital libraries. Many important algorithms broken down and illustrated in pseudo code. Appropriate for use by engineers as a comprehensive reference to the computer vision enterprise.
3,627 citations
Book•
01 Mar 2005
1,285 citations