Digital Image Processing Quiz
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Which of the following is NOT an application of image processing?

  • Medical Imaging
  • Document Editing (correct)
  • Remote Sensing
  • Computer Vision

    • A pixel is the largest unit of a digital image.

    False

    What does digital image processing help computers do with visual information?

    Understand and make decisions

    In digital imaging, each pixel represents a property such as brightness or ______.

    <p>color</p> Signup and view all the answers

    Match the following applications of image processing with their descriptions:

    <p>Medical Imaging = Segmentation for diagnosis Biometrics = Face and fingerprint recognition Remote Sensing = Satellite image analysis Robotics = Object tracking in industrial robots</p> Signup and view all the answers

    Which of the following best describes a digital image?

    <p>A representation of a real image as a set of numbers</p> Signup and view all the answers

    Image processing is solely used for enhancing image quality.

    <p>False</p> Signup and view all the answers

    What are the small areas that images are divided into called?

    <p>Pixels</p> Signup and view all the answers

    What is the primary color model used in color images?

    <p>RGB</p> Signup and view all the answers

    In a grayscale image, each pixel's value can represent a color.

    <p>False</p> Signup and view all the answers

    What does bit depth refer to?

    <p>The number of bits used to represent the color of a single pixel.</p> Signup and view all the answers

    A ___ image contains only two colors: black and white.

    <p>binary</p> Signup and view all the answers

    Match the image formats to their characteristics:

    <p>PNG = Lossless format supporting transparency JPEG = Lossy format optimized for photographs TIFF = Lossless format used in professional imaging BMP = Uncompressed format with large file sizes</p> Signup and view all the answers

    What command is used to install OpenCV in Python?

    <p>pip install opencv-python</p> Signup and view all the answers

    Higher resolution images have less detail compared to lower resolution images.

    <p>False</p> Signup and view all the answers

    What are the names of the three channels in the RGB color model?

    <p>Red, Green, Blue</p> Signup and view all the answers

    What does 'saturation' refer to in the HSV color model?

    <p>The intensity of the color</p> Signup and view all the answers

    Grayscale images consist of multiple color channels.

    <p>False</p> Signup and view all the answers

    What is the purpose of cropping an image?

    <p>To extract a region of interest from the image by cutting out a specific area.</p> Signup and view all the answers

    The ______ transformation matrix is used for rotating an image.

    <p>rotation</p> Signup and view all the answers

    Which interpolation method is NOT commonly used for resizing images?

    <p>Median Filter</p> Signup and view all the answers

    Match the following image transformations with their descriptions:

    <p>Resizing = Changing dimensions of the image Flipping = Mirroring the image horizontally or vertically Rotating = Turning the image around its center Cropping = Extracting a specific area from the image</p> Signup and view all the answers

    Bilateral Filter is used for reducing noise without preserving edges.

    <p>False</p> Signup and view all the answers

    Define 'blurring' in the context of image filtering.

    <p>Blurring reduces image details and smooths the image by averaging pixel values.</p> Signup and view all the answers

    What is the purpose of sharpening in image processing?

    <p>To enhance edges and fine details</p> Signup and view all the answers

    Gaussian blur is a technique used for edge detection.

    <p>False</p> Signup and view all the answers

    What is the main difference between simple thresholding and adaptive thresholding?

    <p>Simple thresholding applies a single threshold value, while adaptive thresholding uses varying thresholds based on local regions.</p> Signup and view all the answers

    The process of applying a kernel to an image is known as __________.

    <p>image filtering</p> Signup and view all the answers

    Match the following filtering techniques with their descriptions:

    <p>Canny = Multi-step edge detection algorithm Sobel = Calculates gradients in horizontal and vertical directions Gaussian Blur = Noise reduction technique using a bell-shaped curve Median Filtering = Removes noise by replacing each pixel with the median of its neighbors</p> Signup and view all the answers

    What is an image histogram used for?

    <p>To show the intensity distribution of an image</p> Signup and view all the answers

    The output of applying a kernel is referred to as the filtered image.

    <p>True</p> Signup and view all the answers

    What do bins represent in an image histogram?

    <p>Bins represent the number of pixels corresponding to each pixel value in the image.</p> Signup and view all the answers

    What is the primary purpose of contour detection in image processing?

    <p>To detect objects and their boundaries</p> Signup and view all the answers

    Thresholding is not a method used for converting images to binary before contour detection.

    <p>False</p> Signup and view all the answers

    What algorithm is mentioned as being used in OpenCV for contour extraction?

    <p>Suzuki and Abe’s algorithm</p> Signup and view all the answers

    To find the count of objects in an image, the first step is to read the image and convert it to __________.

    <p>grayscale</p> Signup and view all the answers

    Match the following steps with their purposes in the contour detection process:

    <p>Read the image = Initial step to obtain image data Blur image = Reduce noise and improve edge detection Detect edges = Identify boundaries of objects Dilate image = Connect broken edges for better contour detection</p> Signup and view all the answers

    What is the primary purpose of morphological operations in image processing?

    <p>To process images based on their shapes</p> Signup and view all the answers

    Erosion adds pixels to the boundaries of objects in an image.

    <p>False</p> Signup and view all the answers

    What are the two basic morphological operators?

    <p>Erosion and Dilation</p> Signup and view all the answers

    The process of _________ is a combination of dilation followed by erosion.

    <p>Closing</p> Signup and view all the answers

    Match the morphological operation with its effect:

    <p>Erosion = Removes small white noises and separates connected objects Dilation = Closes small holes within objects Opening = Removes small objects while keeping larger shapes intact Closing = Fills small holes inside objects</p> Signup and view all the answers

    What effect does Dilation have on an object in an image?

    <p>Expands the objects' boundaries</p> Signup and view all the answers

    The gradient in morphological operations is the average of dilation and erosion.

    <p>False</p> Signup and view all the answers

    What is the range of intensity values typically measured in image processing?

    <p>[0, 256]</p> Signup and view all the answers

    Study Notes

    Introduction to Image Processing

    • Image processing is a method to perform operations on an image to extract meaningful information, improve image quality, and enable machine understanding of visual information
    • Key applications include medical imaging (MRI, CT, X-rays), computer vision (autonomous vehicles, facial recognition), remote sensing (satellite image analysis), robotics (machine vision), biometrics (face, fingerprint, iris, voice recognition), AR/VR (augmented/virtual reality), photography/film, forensics, optical character recognition (OCR), and gaming.

    Digital Image Basics

    • A digital image is a set of numbers stored by a computer, representing a real image.
    • Images are divided into small areas called pixels, each having numerical values representing properties like brightness or color.
    • Pixels are arranged in rows and columns, corresponding to the vertical and horizontal position in the image.

    Digital Image Basics (Continued)

    • A pixel is the smallest unit of a digital image or display.
    • Grayscale images use a pixel value to represent a shade of gray, typically ranging from 0 (black) to 255 (white)
    • RGB images represent color using Red, Green, and Blue channels, where each pixel contains three values for these colors.
    • Image resolution is the number of pixels in the width and height of an image, higher resolution implying more detail.
    • Bit depth refers to the number of bits used to represent the color of a single pixel, more bits allowing more shades of colors.

    Types of Images

    • Binary images: Each pixel is either black (0) or white (1)
    • Grayscale images: Contain shades of gray, with each pixel having an intensity value.
    • Color images: Typically represented in RGB format, with each pixel containing color information from three channels (Red, Green, Blue).

    Image Formats

    • PNG: Lossless image format for web graphics, supports transparency, optimized for high quality
    • JPEG: Lossy format optimized for photographs, reduces file size at cost of some quality, commonly used for photos.
    • TIFF: Lossless format often used in professional imaging (medical/publishing) due to high quality.
    • BMP: Uncompressed image format with large file sizes but excellent quality, frequently used in Windows applications.

    OpenCV Library

    • OpenCV is an open-source computer vision and machine learning library with over 2500 optimized algorithms covering classic and contemporary computer vision techniques.
    • Install OpenCV in Python using pip: pip install opencv-python

    Basic Operations

    • Loading: Reading an image file from disk into memory.
    • Saving: Writing an image from memory to disk in a specified format.
    • Displaying: Showing an image in a graphical window.

    Color Spaces

    • RGB (Red, Green, Blue): Standard color model
    • HSV (Hue, Saturation, Value): Alternative color representation where hue defines color, saturation defines intensity, and value defines brightness.
    • Grayscale: Converts color images to shades of gray by averaging RGB values.

    Image Transformations

    • Resizing: Changing image dimensions by scaling up/down, often preserving aspect ratio.
    • Cropping: Extracting a region of interest (ROI) from an image by cutting out a specific area.
    • Rotation: Rotating the image around its center by a specified angle.
    • Flipping: Mirroring the image horizontally or vertically.
    • Transformation Matrix: Used for operations like rotation, scaling, and translation; mapping points to another coordinate system to modify the geometric properties of an image.
    • Rotation Transformation Matrix: Used to rotate points around the origin by a specific angle using trigonometric functions.

    Image Filtering

    • Blurring: Reduces image details, smoothing by averaging pixel values, used to reduce noise.
      • Gaussian Blur: Weighted smoothing with a bell curve.
      • Mean Filter: Simple averaging.
      • Median Filter: Noise reduction without blurring, good for salt-pepper noise.
      • Bilateral Filter: Smoothing while preserving edges.
      • LoG: Edge detection combining smoothing.
    • Sharpening: Enhances edges and fine details by amplifying differences between neighboring pixels.
    • Noise Reduction: Removes unwanted random variations (noise) from images using techniques like Gaussian blur or median filtering.
    • Edge Detection (Canny, Sobel): Algorithms for identifying edges based on gradient intensities and thresholds.

    Report Task 1

    • Prepare a report covering interpolation techniques and Canny/Sobel algorithms
    • Create a simple Python program to apply Canny edge detection to a video.

    Image Processing in OpenCV (2D Convolution)

    • 2D convolution involves applying a kernel (small matrix of weights) over input data while performing element-wise multiplication and summing up the results for each output pixel.
    • The kernel is called the image filter making the process image filtering where the result (or filtered output) is called i.

    Image Thresholding

    • Simple Thresholding: A straightforward method where each pixel's value is compared to a single threshold value, setting the pixel to 0 if below the threshold or maximum value if above.
    • Adaptive Thresholding: An algorithm that determines the threshold for each pixel based on a local region around it. This provides better results for images with uneven lighting.

    Image Histogram

    • A histogram is a graph that shows the distribution of pixel intensities in an image.
    • Bins display the number of pixels for each pixel value (typically 0-255).
    • Dims refer to the number of parameters measured, often just intensity values in a single-channel image.
    • The range of values typically used is 0 to 256.

    Morphological Transformations

    • Morphological operations are image processing techniques that process images based on their shapes, commonly used with binary (black and white) or grayscale images.
    • Key operations include erosion (reducing object size), dilation (enlarging object size), opening (reducing noise while maintaining object shapes), closing (filling holes and gaps within objects), and gradient (outline of objects).

    Contours

    • Contours are the outlines of objects or shapes in an image, expressed as curves connecting continuous points of similar intensity.
    • Methods for contour detection include thresholding or edge detection, followed by contour extraction using algorithms that identify and trace these curves.
    • Contour detection is used in object detection and identification.

    Report Task 2

    • Report on Counting Objects:
      1. Read image, convert to grayscale
      2. Blur image
      3. Detect edges
      4. Dilate image to connect edges
      5. Find contours
      6. Count detected objects

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    Image Processing Lab PDF

    Description

    Test your knowledge on digital image processing concepts, applications, and terminologies. This quiz covers pixel representation, color models, and OpenCV in Python. Challenge yourself and see how well you understand the fundamentals of image processing!

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