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image processing

Transcript: Image processing is the editing of images. You can use different apps to do this. You can use apps to make the pictures, and apps to edit the pictures. by Sophie, Eva, Nicole and Elora What is image processing? Apps You can use different apps to edit images. For this you first need to have a picture. You can make this also with a special app. For example Snapchat. This is also the main app for our presentation. So if you want to make a picture with snapchat, you do it like this: Eva shows how to make a picture with snapchat. As you have seen, you can use Snapchat in a very easy way. You can really easy get a filter in a picture. The filters on Snapchat are not always the same. Everyday one filter is gone, and then another new filter comes. So you have not always the same filters. After you took the picture, you can give it another kind of filter. Like a kind of shine or something. You can also add text or colour on your picture. Eva show how to give your picture a filter, text and colour. If your picture is done, you can send it. You can add friends and sent your pictures to them. Or you can place your picture on your story, and then all your friends can see it. image processing

Image Processing

Transcript: Outline: 1. Downloading images from: a. Flash Drive b. Internet c. Mobile Phones/Camera 2. Inserting images in: a. Writer b. Impress c. Calc Downloading Images from the Mobile Phones/Camera 1. Plug the USB cable in the device. 2. Insert the USB cable in the computer/laptop. 2. Open the folder where your images are. - My Computer -> F: or G: or H: 3. Copy the desired images. 4. Paste to another folder on your computer. For example: Desktop Resizing your Image 1. Click the image you want to resize. 2. Point to any edge of the image. You can notice a two-way arrow appears. 3. Drag to resize. Photo credits: 'horizon' by pierreyves @ flickr The position of the image relative to this anchor. Downloading images from the Internet 1. Open Google Images in your Internet browser. Type in the object you want and press enter. 2. Click the desired image. 3. Click Full-size Image. 4. Right click image then select save image as. Save to desired file location. For example: Desktop The Wrap setting determines the relation between the text and the image. ` Alignment in Writer and Impress 1. Open your Open Office (Writer/Impress/Calc) Start -> All Programs -> Open Office -> Writer/Impress/Calc 2. To insert an image: Insert -> Picture -> From File -> [choose file] Image Processing Flipping in Calc and Impress 1. Right click image. 2. Select Flip. 3. Select either vertically or horizontally. Wrapping options of Writer 1. Right click image. 2. Select Wrap. 3. Choose from the following: a. No Wrap b. (Optimal) Page Wrap c. Wrap Through Flipping in Writer 1. Right click image. 2. Select Picture. 3. Click the Picture tab. 4. Check either vertically or/and horizontally. 5. Click OK. Flipping Images To flip an image is to rotate it vertically or horizontally. Flash Drive (USB) 1. Insert your Flash Drive in the computer/laptop. 2. Open the folder where your images are. - My Computer -> F: or G: or H: 3. Copy the desired images. 4. Paste to another folder on your computer. For example: Desktop Wrapping Text Around Images 1. Right click image. 2. Select Alignment. 3. Choose from the following: a. Center b. Left c. Right 4. Or, you can just drag the image to align. Downloading Images from External Drivers Inserting Images to Open Office Image Alignment

Image Processing

Transcript: Applications in the Real World Tesla Autopilot (Self Driving Car) 1. Analog 2. Digital -Biomedical Imaging -Astronomical Image Processing -Security By: Samritha Balamoni Image Processing Training/Education to Pursue a Career in Image Processing Definition: --As of now in the market, candidates should be skilled in C/C++,Python, MATLAB and other related programs. Current Developments Interesting Facts Goals in Image Processing: Image processing is the process of analysing an image with the help of algorithms to identify certain characteristics within the picture such as colours, shades and other results which may not be perceived by the human eye. -Glasses that could help the blind "see" - Object tracking Types of Image Processing: Introduction and Relation to Computer Science --At UofT, you can do your MENG with an emphasis in Mechatronics and Robotics which will allow you to explore advanced performance systems such as systems integration, control systems, signal and image processing, dynamics and modeling. 1. Image Resolution and Restoration 2. Image Recognition 3. Visualization

Image Processing

Transcript: Adnan Shakeel Ahmed 2016-333-008 BTECE LS Image Processing What is an Image?! Image Digital Image Digital Image Sampling Quantization Sampling & Quantization Image Processing Image Processing Range of f: Domain of f: Operations Log Negative Image Enhancement Image Histograms Histogram Equalization Contrast Stretching Applications Image Enhancement Interpretation of Aerial Photography Target Recognition Medicine Law Enforcement Key Stages Key Stages Image Acquisition Image Acquisition Image Enhance Image Enhancement Image Restore Image Restoration Morphological Processing Segmentation Object Recognition Representation and Description Image Compression Colour Image Processing R. Gonzalez and R. Woods, “Digital Image Processing – 2n d Edition”, Prentice Hall, 2002 • C. Garcia et al., “Face Detection in Color Images Using Wavelet Packet Analysis”. • “Machine Vision: Automated Visual Inspection and Robot Vision”, David Vernon, Prentice Hall, 1991 Available online at: homepages.inf.ed.ac.uk/rbf/BOOKS/VERNON/ Content Source Reference

Image processing

Transcript: Facial Imperfection Region Detection & Segmentation By: Hussa Alrumaih Introduction 1 Introduction Image-processing based facial imperfection region detection and segmentation Authers: Jaepil Ko Kyung Joo Cheoi Publish year: 23 Feb 2021 The problem: Visiting a clinic to determine skin condetion is costly. The solotion: An image-processing based system that detects facial imperfection regions such as wrinkles moles, etc. Proposed system 2 Proposed system Illumination removal using LAB color model 1. Illumination removal using LAB color model What is Illumination? How dose it work? What is LAB channel? 1. L-channel Image Extraction. 2. Median filtering onto L-channel Image. 3. Negative image of 2. 4. add 2 to 3. 5. convert it to RGB Image. L channel: Black & White A Channel: Red & grean B Channel: Blue & Yallow 2. Facial skin area extraction Facial skin area extraction Face detection: 1. Face detection They used the Harr-like feature classifier that detects the nose and estimats the position and size of the face. Skin color detection 2. Skin color detection They used HSV and YCbCr color spaces because it has a uniform characteristics. Then they used a threshold as follow: 0.1≤S ≤0.7 0.2≤V≤1.0 73≤Cb ≤138 102≤Cr ≤173 Then they used K-mean algorithm to cluster it to 3 clusters: background, hair, and skin. Eye and mouth removal 3. Eye and mouth removal 1. histogram equalization: When the histogram equalization is applied, the difference between the intensities in the eyes and the mouth increases. 2. Using this difference, the eye, nose, and mouth regions are extracted by the equation: Pr( x, y) - Raverage ≥ 1 Pr=value of red, Raverage= average of red pixels Pg(x, y) < 107 Pg= value of grean pixel. Pb(x, y) < 66 Pb= value of blue pixel. 3. Reactivity calculation of discontinuous region using Gabor filter Reactivity calculation of discontinuous region using Gabor filter What is Gabor filter? A filter used adaptively to the change of scale and direction to effectively detect information about complex textures such as skin imperfections. They set the prameter to: g(x,y: 0.8, [0, π/6, π/4, π/3, π/2, 2π/3 3π/4, 5π/6], 9, π/2) Segmentation of discontinuous region using DBSCAN Segmentation of discontinuous region using DBSCAN What is DBSCAN? Density-based spatial clustering of applications with noise. The advantage of DBSCAN is that: number of clusters doesn’t need to be determined. It classify clusters of arbitrary shapes, including the concept of noise. Experimental images 3 In this paper, they used: Facial Images of people with age range from 20 to 50. 8 different kinds of datasets and each dataset consists of 20 images, total of 160. They will evalute the system using Ground Truth by comparing the system output to the ground truth value, then calcuate its accuracy. Experimental images Results & discussion 4 Results and discussion They compared the results with ground truth. If the system correctly detected more than 70% of the imperfection area, it was judged that the system detected successfully. Accuracy was found to be more than 90% Experimental results Original Image comparison with other methodes Canny edge detector proposed method Original Image Alamdari’s method proposed method Conclusions 5 Conclusions 6 Thank you Thank you!

Image Processing

Transcript: By : Menna Badr Face Recognition Thank You Pattern Recognition Image Processing Photography and Film Making Medical usage What is image Processing? 1- Face Recognition 2- Fingerprint 3- Medical Usage and more

Image Processing

Transcript: Magnetic Resonance Imaging (MRI): The radio waves pass through a patient’ body in short pulses, which is kept in a high magnetic field. Each pulse causes a responding pulse emitted by the patient’s tissue. The signal origin and strength are determined by a computer, which produces a two dimensional image of a section of the patient. Ultrasound imaging used mainly in obstetrics. Basic procedure in ultrasound imaging: Ultrasound system transmits high-frequency (1 to 5 MHz) sound pulses into the body. The sound waves travel into the body and hit a boundary between tissues (e.g., soft tissue and bone). Some of the sound waves are reflected back to the probe, while some travel on further until they reach another boundary. Nuclear medicine: inject the patient with a radioactive isotope that emits gamma rays. Images are produced from the emissions collected by gamma ray detectors. Applications Automatic Character Recognition Industrial Machine Vision for product assembly and inspection Military recognizance Automatic processing of fingerprints Screening of X-Rays and blood samples Machine processing of aerial and satellite images for weather prediction and crop assessment Image Processiong Types of signals Applications In Physics Enhance images of experiments in areas such as high-energy plasmas and electron microscopy. Other Application Areas Law Enforcement Defence Industrial Applications (E.g. Vision based automation) Surveillance Biology X-rays are used extensively in medical imaging and in industry. X-ray tube: a cathode which is heated and releases electrons. Electrons fly at high speed to the positively charged anode. When the electrons strike a nucleus, energy is released in the form of X-ray radiation. The intensity of the X-ray is modified by absorption as it passes through the patient. 1D-Signals Voice signals ECG and EEG Signals Gamma-ray Imaging PET 1-Dimensional 2-Dimensional and 3-Dimensional Signals Acoustic Imaging (Continued) MRI Imaging in Visible Band Introduction Ultraviolet light is used in fluorescence microscopy. Fluorescence: a phenomena in which some material (called fluorescent) emit visible light when ultraviolet light is directed at them. The reflected waves are picked by the probe and relayed to a computer. The computer calculates the distance from the probe to the tissue using the speed of sound in tissue. The system displays the distance and intensities of the echoes on the screen, forming a two-dimensional image. In Medicine Enhance the contrast or code the intensity levels into colour for easier representation of X-Rays and other Bio-Medical Images In Geography Study pollution patterns from aerial and satellite imagery. In Archaeology Used to process degraded images of unrecoverable objects or experimental results too expensive to duplicate Restoration of blurred pictures that were the only available records of rare artefacts lost or damaged after being photographed. 2D- Signals 1D Signal Examples Imaging in the Ultraviolet (UV) Band Positron Emission Tomography (PET): the patient is given a radioactive isotope that emits positron. Positron generates gamma rays which are detected and an image is created. Imaging in the Microwave Band The dominant application of imaging in the microwave band is radar, where radar works like a flash camera. Unique feature: able to collect data over virtually any region at any time regardless of weather or lighting condition. Applications Remote sensing: to obtain images of the earth from space for purposes of monitoring environmental conditions Usually a scene is imaged in several bands Imaging in Visibible Band Acoustic (Ultrasound) Imaging Automated visual inspection of manufactured goods Processing of fingerprints for automated search of a database Automated license plate reading X-ray Imaging

Image Processing

Transcript: Image Processing Project of MAT 210 Presenter:- Shankar Ale and Wilson Professor:- 21/05/22 INTRODUCTION INTRODUCTION Digital images are made of pixels and each pixel contains numerical values that can be interpreted as the color in that part of the image. Linear Algebra and Image processing are like two sides of same coin. An image can be represented as a matrix and linear operations like matrix addition, subtraction, multiplication, etc., can be performed on them, these are called Image Filters. FORMATION Mission Statement The images you see on internet pages and the photos you take with your mobile phone are examples of digital images. Matrices representation can be used for this digital images. As we all know that computer only takes 1s and 0s. These binary numbers are converted into decimal and represented in matrices to form different color. Our Locations Our Locations Organization Organization Product Product Our Projects Our Projects Product 1 Detail Product 1 Detail Product 2 Detail Product 2 Detail Our Team Our Team Marketing Marketing Campaigns Campaigns Our Team Our Team Sales Sales Current Standings Current Standings Our Team Our Team What's Next? What's Next? Finance Finance Overview Overview Our Team Our Team

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