This document provides an introduction and overview of image processing using Matlab. It discusses the basics of Matlab including its environment, syntax, variables, vectors and matrices. It then covers image processing topics such as importing and exporting images, viewing histograms, and applying filters like box filters and linear filters to images. The document is intended to teach the fundamentals of working with images in the Matlab programming language.
The document provides an overview of basic image processing functions in MATLAB. It discusses how images are represented in MATLAB as 2D or 3D arrays, describes common image data types like uint8 and double. It also summarizes some basic functions for reading, displaying and manipulating images like imread(), imshow(), manipulating color channels, and rescaling images. Examples demonstrate converting between data types, scaling images, color space conversions to grayscale, and simple image blurring.
It is the basic introduction of how the images will be captured and converted form analog to digital format by using sampling and quantization process and further algorithms will be apply on the digitized image.
This document provides an overview of using MATLAB for image processing. It describes MATLAB's development environment and basic data structures. It also covers reading, displaying, and saving images, as well as common image processing techniques like point processing, histogram equalization, and color space conversion that can be performed in MATLAB.
Digital image processing using matlab (fundamentals)Taimur Adil
The document provides an overview of digital image processing using MATLAB. It covers topics such as reading and displaying images, image formats, data types, array and matrix indexing, standard array functions, operators, and flow control statements. Examples are given for how to use various MATLAB functions to load, manipulate, and process image data.
This document presents information on linear filtering and its use for image enhancement. It discusses using the fspecial and imfilter commands in MATLAB to apply various 2D filters to images, including median filters and filters for blurring, sharpening, and approximating camera motion. Examples are provided to demonstrate applying motion blurring, blurring, sharpening, and noise reduction filters to images. The objectives are to use 2D median filtering and filter multidimensional images.
This document provides an overview of digital image processing. It discusses what image processing entails, including enhancing images, extracting information, and pattern recognition. It also describes various image processing techniques such as radiometric and geometric correction, image enhancement, classification, and accuracy assessment. Radiometric correction aims to reduce noise from sources like the atmosphere, sensors, and terrain. Geometric correction geometrically registers images. Image enhancement improves interpretability. Classification categorizes pixels. The document outlines both supervised and unsupervised classification methods.
This document provides an introduction and overview of image processing using Matlab. It discusses the basics of Matlab including its environment, syntax, variables, vectors and matrices. It then covers image processing topics such as importing and exporting images, viewing histograms, and applying filters like box filters and linear filters to images. The document is intended to teach the fundamentals of working with images in the Matlab programming language.
The document provides an overview of basic image processing functions in MATLAB. It discusses how images are represented in MATLAB as 2D or 3D arrays, describes common image data types like uint8 and double. It also summarizes some basic functions for reading, displaying and manipulating images like imread(), imshow(), manipulating color channels, and rescaling images. Examples demonstrate converting between data types, scaling images, color space conversions to grayscale, and simple image blurring.
It is the basic introduction of how the images will be captured and converted form analog to digital format by using sampling and quantization process and further algorithms will be apply on the digitized image.
This document provides an overview of using MATLAB for image processing. It describes MATLAB's development environment and basic data structures. It also covers reading, displaying, and saving images, as well as common image processing techniques like point processing, histogram equalization, and color space conversion that can be performed in MATLAB.
Digital image processing using matlab (fundamentals)Taimur Adil
The document provides an overview of digital image processing using MATLAB. It covers topics such as reading and displaying images, image formats, data types, array and matrix indexing, standard array functions, operators, and flow control statements. Examples are given for how to use various MATLAB functions to load, manipulate, and process image data.
This document presents information on linear filtering and its use for image enhancement. It discusses using the fspecial and imfilter commands in MATLAB to apply various 2D filters to images, including median filters and filters for blurring, sharpening, and approximating camera motion. Examples are provided to demonstrate applying motion blurring, blurring, sharpening, and noise reduction filters to images. The objectives are to use 2D median filtering and filter multidimensional images.
This document provides an overview of digital image processing. It discusses what image processing entails, including enhancing images, extracting information, and pattern recognition. It also describes various image processing techniques such as radiometric and geometric correction, image enhancement, classification, and accuracy assessment. Radiometric correction aims to reduce noise from sources like the atmosphere, sensors, and terrain. Geometric correction geometrically registers images. Image enhancement improves interpretability. Classification categorizes pixels. The document outlines both supervised and unsupervised classification methods.
Digital Image Processing (Lab 09 and 10)Moe Moe Myint
The document discusses digital image processing using MATLAB. It covers topics like linear filtering, transforms, morphological operations and provides examples of using the dct2 and idct2 commands to compute the discrete cosine transform and inverse discrete cosine transform. It also demonstrates commands like imclose to morphologically close an image, imdilate to dilate an image, and imerode to erode an image providing syntax and examples for each. The document is presented by Dr. Moe Moe Myint from Technological University in Myanmar.
Traffic jam detection using image processingSai As Sharman
This document presents a traffic jam detection system using image processing. The system uses cameras to capture video frames of traffic at regular intervals. The frames are analyzed using image processing techniques like grayscale conversion, erosion, and dilation to detect vehicles and motion. An android application is also developed to provide users with real-time traffic density information for different locations based on the image analysis. The proposed system aims to provide a low-cost and reliable alternative to existing magnetic and infrared-based traffic detection methods.
Lecture 1 for Digital Image Processing (2nd Edition)Moe Moe Myint
-What is Digital Image Processing?
-The Origins of Digital Image Processing
-Examples of Fields that Use Digital Image Processing
-Fundamentals Steps in Digital Image Processing
-Components of an Image Processing System
This document provides an overview of real-time image processing. It begins with introducing real-time image processing and how it differs from ordinary image processing by having deadlines and predictable response times. The document then discusses the requirements for a real-time image processing system including high resolution video input, low latency, and high processing performance. It also covers applications such as mobile robots and human-computer interaction. In the end, it provides definitions of real-time image processing in both the perceptual and signal processing senses.
The document provides an overview of basic image processing concepts and techniques using MATLAB, including:
- Reading and displaying images
- Performing operations on image matrices like dilation, erosion, and thresholding
- Segmenting images using global and local thresholding methods
- Identifying and labeling connected components
- Extracting properties of connected components using regionprops
- Performing tasks like edge detection and noise removal
Code examples and explanations are provided for key functions like imread, imshow, imdilate, imerode, im2bw, regionprops, and edge.
Introduction to digital image processing, image processing, digital image, analog image, formation of digital image, level of digital image processing, components of a digital image processing system, advantages of digital image processing, limitations of digital image processing, fields of digital image processing, ultrasound imaging, x-ray imaging, SEM, PET, TEM
This presentation discusses digital image processing. It begins with definitions of digital images and digital image processing. Digital image processing focuses on improving images for human interpretation and processing images for machine perception. The history of digital image processing is then reviewed from the 1920s to today. Key examples of applications like medical imaging, satellite imagery, and industrial inspection are provided. The main stages of digital image processing are outlined, including image acquisition, enhancement, restoration, segmentation, and compression. The document concludes with an overview of a system for automatic face recognition using color-based segmentation.
This presentation was provided by Rebecca Benner, Ph.D., of the American Society of Anesthesiologists, for the second session of NISO's 2024 Training Series "DEIA in the Scholarly Landscape." Session Two: 'Expanding Pathways to Publishing Careers,' was held June 13, 2024.
A Visual Guide to 1 Samuel | A Tale of Two HeartsSteve Thomason
These slides walk through the story of 1 Samuel. Samuel is the last judge of Israel. The people reject God and want a king. Saul is anointed as the first king, but he is not a good king. David, the shepherd boy is anointed and Saul is envious of him. David shows honor while Saul continues to self destruct.
Gender and Mental Health - Counselling and Family Therapy Applications and In...PsychoTech Services
A proprietary approach developed by bringing together the best of learning theories from Psychology, design principles from the world of visualization, and pedagogical methods from over a decade of training experience, that enables you to: Learn better, faster!
Temple of Asclepius in Thrace. Excavation resultsKrassimira Luka
The temple and the sanctuary around were dedicated to Asklepios Zmidrenus. This name has been known since 1875 when an inscription dedicated to him was discovered in Rome. The inscription is dated in 227 AD and was left by soldiers originating from the city of Philippopolis (modern Plovdiv).
Elevate Your Nonprofit's Online Presence_ A Guide to Effective SEO Strategies...TechSoup
Whether you're new to SEO or looking to refine your existing strategies, this webinar will provide you with actionable insights and practical tips to elevate your nonprofit's online presence.
This presentation was provided by Racquel Jemison, Ph.D., Christina MacLaughlin, Ph.D., and Paulomi Majumder. Ph.D., all of the American Chemical Society, for the second session of NISO's 2024 Training Series "DEIA in the Scholarly Landscape." Session Two: 'Expanding Pathways to Publishing Careers,' was held June 13, 2024.
Digital Image Processing (Lab 09 and 10)Moe Moe Myint
The document discusses digital image processing using MATLAB. It covers topics like linear filtering, transforms, morphological operations and provides examples of using the dct2 and idct2 commands to compute the discrete cosine transform and inverse discrete cosine transform. It also demonstrates commands like imclose to morphologically close an image, imdilate to dilate an image, and imerode to erode an image providing syntax and examples for each. The document is presented by Dr. Moe Moe Myint from Technological University in Myanmar.
Traffic jam detection using image processingSai As Sharman
This document presents a traffic jam detection system using image processing. The system uses cameras to capture video frames of traffic at regular intervals. The frames are analyzed using image processing techniques like grayscale conversion, erosion, and dilation to detect vehicles and motion. An android application is also developed to provide users with real-time traffic density information for different locations based on the image analysis. The proposed system aims to provide a low-cost and reliable alternative to existing magnetic and infrared-based traffic detection methods.
Lecture 1 for Digital Image Processing (2nd Edition)Moe Moe Myint
-What is Digital Image Processing?
-The Origins of Digital Image Processing
-Examples of Fields that Use Digital Image Processing
-Fundamentals Steps in Digital Image Processing
-Components of an Image Processing System
This document provides an overview of real-time image processing. It begins with introducing real-time image processing and how it differs from ordinary image processing by having deadlines and predictable response times. The document then discusses the requirements for a real-time image processing system including high resolution video input, low latency, and high processing performance. It also covers applications such as mobile robots and human-computer interaction. In the end, it provides definitions of real-time image processing in both the perceptual and signal processing senses.
The document provides an overview of basic image processing concepts and techniques using MATLAB, including:
- Reading and displaying images
- Performing operations on image matrices like dilation, erosion, and thresholding
- Segmenting images using global and local thresholding methods
- Identifying and labeling connected components
- Extracting properties of connected components using regionprops
- Performing tasks like edge detection and noise removal
Code examples and explanations are provided for key functions like imread, imshow, imdilate, imerode, im2bw, regionprops, and edge.
Introduction to digital image processing, image processing, digital image, analog image, formation of digital image, level of digital image processing, components of a digital image processing system, advantages of digital image processing, limitations of digital image processing, fields of digital image processing, ultrasound imaging, x-ray imaging, SEM, PET, TEM
This presentation discusses digital image processing. It begins with definitions of digital images and digital image processing. Digital image processing focuses on improving images for human interpretation and processing images for machine perception. The history of digital image processing is then reviewed from the 1920s to today. Key examples of applications like medical imaging, satellite imagery, and industrial inspection are provided. The main stages of digital image processing are outlined, including image acquisition, enhancement, restoration, segmentation, and compression. The document concludes with an overview of a system for automatic face recognition using color-based segmentation.
This presentation was provided by Rebecca Benner, Ph.D., of the American Society of Anesthesiologists, for the second session of NISO's 2024 Training Series "DEIA in the Scholarly Landscape." Session Two: 'Expanding Pathways to Publishing Careers,' was held June 13, 2024.
A Visual Guide to 1 Samuel | A Tale of Two HeartsSteve Thomason
These slides walk through the story of 1 Samuel. Samuel is the last judge of Israel. The people reject God and want a king. Saul is anointed as the first king, but he is not a good king. David, the shepherd boy is anointed and Saul is envious of him. David shows honor while Saul continues to self destruct.
Gender and Mental Health - Counselling and Family Therapy Applications and In...PsychoTech Services
A proprietary approach developed by bringing together the best of learning theories from Psychology, design principles from the world of visualization, and pedagogical methods from over a decade of training experience, that enables you to: Learn better, faster!
Temple of Asclepius in Thrace. Excavation resultsKrassimira Luka
The temple and the sanctuary around were dedicated to Asklepios Zmidrenus. This name has been known since 1875 when an inscription dedicated to him was discovered in Rome. The inscription is dated in 227 AD and was left by soldiers originating from the city of Philippopolis (modern Plovdiv).
Elevate Your Nonprofit's Online Presence_ A Guide to Effective SEO Strategies...TechSoup
Whether you're new to SEO or looking to refine your existing strategies, this webinar will provide you with actionable insights and practical tips to elevate your nonprofit's online presence.
This presentation was provided by Racquel Jemison, Ph.D., Christina MacLaughlin, Ph.D., and Paulomi Majumder. Ph.D., all of the American Chemical Society, for the second session of NISO's 2024 Training Series "DEIA in the Scholarly Landscape." Session Two: 'Expanding Pathways to Publishing Careers,' was held June 13, 2024.
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إضغ بين إيديكم من أقوى الملازم التي صممتها
ملزمة تشريح الجهاز الهيكلي (نظري 3)
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تتميز هذهِ الملزمة بعِدة مُميزات :
1- مُترجمة ترجمة تُناسب جميع المستويات
2- تحتوي على 78 رسم توضيحي لكل كلمة موجودة بالملزمة (لكل كلمة !!!!)
#فهم_ماكو_درخ
3- دقة الكتابة والصور عالية جداً جداً جداً
4- هُنالك بعض المعلومات تم توضيحها بشكل تفصيلي جداً (تُعتبر لدى الطالب أو الطالبة بإنها معلومات مُبهمة ومع ذلك تم توضيح هذهِ المعلومات المُبهمة بشكل تفصيلي جداً
5- الملزمة تشرح نفسها ب نفسها بس تكلك تعال اقراني
6- تحتوي الملزمة في اول سلايد على خارطة تتضمن جميع تفرُعات معلومات الجهاز الهيكلي المذكورة في هذهِ الملزمة
واخيراً هذهِ الملزمة حلالٌ عليكم وإتمنى منكم إن تدعولي بالخير والصحة والعافية فقط
كل التوفيق زملائي وزميلاتي ، زميلكم محمد الذهبي 💊💊
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Andreas Schleicher presents PISA 2022 Volume III - Creative Thinking - 18 Jun...EduSkills OECD
Andreas Schleicher, Director of Education and Skills at the OECD presents at the launch of PISA 2022 Volume III - Creative Minds, Creative Schools on 18 June 2024.
THE SACRIFICE HOW PRO-PALESTINE PROTESTS STUDENTS ARE SACRIFICING TO CHANGE T...indexPub
The recent surge in pro-Palestine student activism has prompted significant responses from universities, ranging from negotiations and divestment commitments to increased transparency about investments in companies supporting the war on Gaza. This activism has led to the cessation of student encampments but also highlighted the substantial sacrifices made by students, including academic disruptions and personal risks. The primary drivers of these protests are poor university administration, lack of transparency, and inadequate communication between officials and students. This study examines the profound emotional, psychological, and professional impacts on students engaged in pro-Palestine protests, focusing on Generation Z's (Gen-Z) activism dynamics. This paper explores the significant sacrifices made by these students and even the professors supporting the pro-Palestine movement, with a focus on recent global movements. Through an in-depth analysis of printed and electronic media, the study examines the impacts of these sacrifices on the academic and personal lives of those involved. The paper highlights examples from various universities, demonstrating student activism's long-term and short-term effects, including disciplinary actions, social backlash, and career implications. The researchers also explore the broader implications of student sacrifices. The findings reveal that these sacrifices are driven by a profound commitment to justice and human rights, and are influenced by the increasing availability of information, peer interactions, and personal convictions. The study also discusses the broader implications of this activism, comparing it to historical precedents and assessing its potential to influence policy and public opinion. The emotional and psychological toll on student activists is significant, but their sense of purpose and community support mitigates some of these challenges. However, the researchers call for acknowledging the broader Impact of these sacrifices on the future global movement of FreePalestine.