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Examen

Solutions Manual for Digital Image Processing and Analysis Computer Vision and Image Analysis, 4th Edition by Scott Umbaugh All Chapters 1 to 7 complete Verified editon ISBN: 9781000788518

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Solutions Manual for Digital Image Processing and Analysis Computer Vision and Image Analysis, 4th Edition by Scott Umbaugh All Chapters 1 to 7 complete Verified editon ISBN: 9781000788518

Institución
Digital Image Processing And Analysis
Grado
Digital Image Processing and Analysis











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Institución
Digital Image Processing and Analysis
Grado
Digital Image Processing and Analysis

Información del documento

Subido en
24 de septiembre de 2025
Número de páginas
149
Escrito en
2025/2026
Tipo
Examen
Contiene
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2

, 3


Solutions Manual for Digital Image Processing and p p p p p p




p Analysis Computer Vision and Image Analysis, 4e by Scott p p p p p p p p




p Umbaugh (All Chapters) p p




Solutions for Chapter 1: Digital Image Processing and Analysis
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1. Digital image processing is also referred to as computer imaging and can be defined as the
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acquisition and processing of visual information by computer. It can be divided into
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application areas of computer vision and human vision; where in computer vision applications
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the end user is a computer and in human vision applications the end user is a human. Image
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analysis ties these two primary application areas together, and can be defined as the
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examination of image data to solve a computer imaging problem. A computer vision system
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can be thought of as a deployed image analysis system.
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2. In general, a computer vision system has an imaging device, such as a camera, and a
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computer running analysis software to perform a desired task. Such as: A system to inspect
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parts on an assembly line. A system to aid in the diagnosis of cancer via MRI images. A system
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to automatically navigate a vehicle across Martian terrain. A system to inspect welds in an
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automotive assembly factory.
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3. The image analysis process requires the use of tools such as image segmentation, image
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transforms, feature extraction and pattern classification. Image segmentation is often one of
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the first steps in finding higher level objects from the raw image data. Feature extraction is the
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process of acquiring higher level image information, such as shape or color information, and
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may
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require the use of image transforms to find spatial frequency information. Pattern classification
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is the act of taking this higher level information and identifying objects within the image.
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4. hardware and software. p p




5. Gigabyte Ethernet, USB 3.2, USB 4.0, Camera Link. p p p p p p p




6. It samples an analog video signal to create a digital image. This sampling is done at a fixed
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rate when it measures the voltage of the signal and uses this value for the pixel brightness. It
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uses the horizontal synch pulse to control timing for one line of video (one row in the digital
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image), and the vertical synch pulse to tell the end of a field or frame
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7. A sensor is a measuring device that responds to various parts of the EM spectrum, or
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other signal that we desire to measure. To create images the measurements are taken
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across a two- dimensional gird, thus creating a digital image.
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8. A range image is an image where the pixel values correspond to the distance from the
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imaging sensor. They are typically created with radar, ultrasound or lasers.
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9. The reflectance function describes the way an object reflects incident light. This relates
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to what we call color and texture it determines how the object looks.
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10. Radiance is the light energy reflected from, or emitted by, an object; whereas irradiance is
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the incident light falling on a surface. So radiance is measured in Power/(Area)(SolidAngle), and
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irradiance is measure in Power./Area.
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11. A photon is a massless particle that is used to model EM radiation. A CCD is a charge-
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coupled device. Quantum efficiency is a measure of how effectively a sensing element
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converts photonic energy into electrical energy, and is given by the ratio of electrical output
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to photonic input.
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1 1 1 p

12. See fig 1.4-5 and use the lens
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p
p
. If the object is at infinity:
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equation:
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a b f

1 p 1 1 p
1 p 1 0
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p
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b f b f
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