You're about to create your best presentation ever

Image Processing Powerpoint Template

Create your presentation by reusing a template from our community or transition your PowerPoint deck into a visually compelling Prezi presentation.

IMAGE PROCESSING

Transcript: DITHERING: Pay for updates GIMP Selects a particular area of an image and discard the portions outside the chosen section Image processing is the use of computer algorithms to perform image processing on digital images. The image processing operation can be modeled in the form of multidimensional systems, because of the 2D - or more- definition of the image. Quantization Ordered Dither Floyd-Steinberg PEN TOOL The editor gives you a bunch of shape tools as polygons, rectangles, ellipses... FILTERING NON LINEAR FILTERING: Selects and area and this area can be edites but the rest of the image won´t suffer any change Transform SHAPE TOOLS : Brushes Different color spaces useful for different operations Full/ In part Duplication Alpha compositing and several color models including RGB, CMYK, CIELAB Adobe Photoshop is a raster graphics editor developed and published by Adobe Systems for macOS and Windows Warp Edit Choses a color from an area of the image that is selected, and samples it for future use The hand tool navigates an image by moving it in any direction Scale Rotate Warp Linux COLOR LASSO: Brightness Contrast Gamma Histogram equalization Composite Morph Computational Photography The pen tool creates precise strokes that can be manipulated using anchor points Free form Pen Tool: Draw paths freehand Magnetic Pen Tool: The drawn path attaches closely to outlines of objects in an image Spot color and duotone IMAGE COMPOSITION Grayscale Saturation White Balance COLOR TRANSFORMATIONS MEASURING AND NAVIGATION LINE Edit and compose raster images in multiple layers and supports masks ADOBE PHOTOSHOP VS GIMP Well known Patterns IMAGE PROCESSING COMBINING IMAGES: BASIC IMAGE PROCESSING OPERATIONS LUMINANCE Lug the entirety of a single layer or more if they are selected Advanced users Selects areas based on pixels of similar values Compatibility Reduce visual artifacts due to quantization Distribute erros among pixels Exploit spatial integration in our eye Duplication of one layer in another layer SELECTION TOOLS: Divides an image into different sections DITHERING VECTOR GRAPHICS ADOBE PHOTOSHOP,GIMP,FILTERS, 2D BEND COMPOSITION OF IMAGES. 2D BEND IN ADOBE PHOTOSHOP WHAT IS ADOBE PHOTOSHOP? Enter MAGIC WAND: SLICING: CROPPING: Free Compatibility MARQUEE: Online Support ERASER: Erases content based on the active layer TRANSFORMATION: Custom selection by drawing it freehand Compute new values for image pixels based on function of old values in neighborhood RECAPITULATION PHOTOSHOP CLONE STAMP TOOL: IMAGE PROCESSING INTRODUCTION Tools not polished Computational photography: Extended depth-of-field High dynamic range images Flash / No flash Stroboscopic images TOOLS MOVING: IMAGE PROCESSING Blur & Sharpen Edge Detection Convolution Professional AR FILTERING Drag the handles Duplicates one part of an image to another part of the same image by way of a brush Median Bilateral Photo montage Removing people

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: SIFT Find the interest points in the image *Later shown on results Characteristic or properties of an image Feauture Finding After we have successfully detect the feature points in both image did in the previously, Now we use those properties in the features to further move close to our goal. A feature vector (descriptor) is used to represent the neighborhood of the interest point. extractFeatures is the command that we used to get the feature descriptors, based on information highlighted by the circular region around the interest point. SURF Advantages MATLAB Implementation Easy to implement Fast Based on Hessian matrix and sums of 2D Haar wavelet response. Better results compared to SIFT and GLOH* Appearance of a feature point can change substantially over several frames Can be mislead soft corners. SURF DISADVANTAGES ORB Construct the scale invariant descriptor on each interest point found in the previous step. Mark Darrelle Garcia (Choco Nut) Liam Aguilar (Choco pie) Roscar John Corpuz (Cream pie) Danielle David San Pedro Gabriel Nocum Arvin Eugenio Read object and whole image using imread command Object Recognition using SURF Gradient Location and Orientation Histogram Thanks for attention Speed- Up Robust Features SURF DETECTOR ALGORITHM FLOW The detectSurFFeatures command returned a surf object for us that will be later used in the next step to extract the feature descriptors. Techniques What is feature? Read Images into workspace Detect feature points Extract Feature Descriptor PUTATIVE POINT MATCH Localization the object The next step in our algorithm is to find the points in both images that tentatively match, with the help of previous step we have been able to extract features descriptors from both images. We use the matchFeatures() command to match the points in both images, by comparing the information content. Then convert images to grayscale SURF Once we have been able to match the points in both image, the matching also match some points that are not neccesary part of the points that contribute to the identity of our template image. These are outliers. Our final step is to eliminate this outliers and localise our template image 1. Form the scale space response by convolving the source image using DoH filters with different σ 2. Search for local maxima across neighbouring pixels and adjacent scales within different octaves 3. Interpolate the location of each local maxima found 4.For each point of interest, return x, y, σ, the DoH magnitude, and the Laplacian’s sign Scale-invariant feature transform Oriented FAST and rotated BRIEF Results IMAGE PROCESSING REPORT, GROUP 4 (DREAM TEAM) GLOH Bay, H., A. Ess, T. Tuytelaars and L. van Gool, 2008. Speeded-Up Robust Features (SURF). Comput. Vision Image Understand., 110 346-359.

Image processing

Transcript: OCR Computing A451 - 4.4 Representing Images Candidates should be able to: Explain the representation of an image as a series of pixels Explain the need for metadata such as height, width and colour depth Discuss the effect of colour depth and resolution on the size of an image file Lesson Plan What do you know? Prezzi, Worksheet Questions Review Finish Digital images are like digital sound recordings – they are ‘samples’ (of light instead of sound) the view is represented by millions of coloured dots called pixels. The higher the density of pixels, the clearer and sharper the image will be. a) Obtaining the edges of an image. 48 219 168 145 49 218 87 94 77 52 108 200 78 798 34 65 -Suitable for fingerprints. What is image processing? What are pixels? • • What is metadata? Can you think of any more? Which image format would be most suitable for a professional photographer? Why? • Why aren’t images in this format on mobile phones? • What is the difference between lossy and lossless file compression -Each pixel is just black or white (one bit per pixel). 2. Render it more suitable for autonomous machine perception. Digital Image Processing for Medical Applications http://hello.processing.org/ c) Removing motion blur from an image. Examples may include: What is a digital image ? -Nuclear medicine -Tomography -Ultrasound How is the resolution of an image measured? What resolution is suitable for a monitor display? Give some examples of image formats. How many bits are used to store the information in each pixel? 1 0 1 1 0 1 0 0 1 1 0 1 1 0 0 2. Greyscale image -Each pixel has a particular color; described by the amount of red, green and blue in it. -Each of the RGB components has a range 0-255, this gives a total of (255^3)= 16, 777, 256 different possible colors in the image. Questions http://www.mathworks.co.uk/products/image/ Picture elements. The small packets of image data that make up the image. Pixels or dots per inch. 72 dpi TIFF, JPEG, GIF, RAW, BMP, PNG. 24. 8 for each of the colours red, green and blue. An information file that is stored with the image. It contains information such as date, geographical coordinates, camera speed and aperture setting. Image processing involves changing the nature of an image in order to either:- a) Enhancing the edges of an image to make it appear sharper. Image Processing Applications Please go to questions 1.Binary image Processing 2 And 3.True color, or RGB image 0 0 55 255 0 55 255 55 55 25 55 55 55 55 55 0 0 0 0 0 A digital image is an array of pixels which are tiny little dots of color you see on your screen, and the smallest possible size any image can get. When an image is stored, the image file contains information on every single pixel in that image. -Each pixel is a shade of grey, from 0 (black) to 255 (white) ((one byte(8 bit) per pixel)). Imaging technology -Suitable for medicine (X-rays). RAW. Uncompressed images and so will contain all of the original image data. Very large file sizes, usually about 50 to 100MB. With lossless compression, the original file can be reconstituted from the compressed data but with lossy compression it cannot. Some of the original data is lost. Examples may include: b) Removing noise from an image. Matlab Image processing Types of digital images:- Medical imaging is the technique and process used to create images of the human body (or parts and function thereof) for clinical purposes (medical procedures seeking to reveal, diagnose or examine disease) or medical science (including the study of normal anatomy and physiology). Thanks for your attention So how? Image Processing Software Picture elements. The small packets of image data that make up the image Please look at the pdf workbook provided

Now you can make any subject more engaging and memorable