Digital Image Processing Course Quiz

False (B)

Medical imaging

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

<p>Image = Dealing with pictorial data Digital = In a digital form on a digital computer Processing = Achieving a specific goal or objective</p> Signup and view all the answers

<p>Audio data processing (B)</p> Signup and view all the answers

<p>3 (B)</p> Signup and view all the answers

<p>True (A)</p> Signup and view all the answers

<p>False (B)</p> Signup and view all the answers

<p>The student may receive a -100% grade, face automatic failure in the course, or possibly expulsion.</p> Signup and view all the answers

<p>Check frequently for updates.</p> Signup and view all the answers

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

<p>Cell phones = Not allowed Food and drinks = Not allowed Laptops = For taking notes only Attendance = Arrive on time</p> Signup and view all the answers

<p>Report to the Office of Dean (C)</p> Signup and view all the answers

<p>0 (B)</p> Signup and view all the answers

<p>False (B)</p> Signup and view all the answers

<p>False (B)</p> Signup and view all the answers

<p>A grid (matrix) of intensity values</p> Signup and view all the answers

<p>Students must read the entire syllabus.</p> Signup and view all the answers

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

<p>0 = Black 127 = Gray 255 = White 20 = Dark Gray</p> Signup and view all the answers

<p>Color Constancy (B)</p> Signup and view all the answers

<p>True (A)</p> Signup and view all the answers

<p>Color constancy</p> Signup and view all the answers

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

<p>Image Segmentation = Dividing an image into its constituent parts or objects Morphological Image Processing = Processing shapes and structures within an image Image Restoration = Recovering an image that has been degraded Fourier Transform = Transforming an image to analyze frequency components</p> Signup and view all the answers

<p>Color Image Processing (C)</p> Signup and view all the answers

<p>False (B)</p> Signup and view all the answers

<p>Image segmentation or Image classification</p> Signup and view all the answers

<p>It encompasses processes where both inputs and outputs are images. (A)</p> Signup and view all the answers

<p>False (B)</p> Signup and view all the answers

<p>There is no general agreement among authors regarding where image processing stops and other areas start.</p> Signup and view all the answers

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

<p>Low-level processes = Basic image enhancement techniques Mid-level processes = Extraction of features from images High-level processes = Recognition and interpretation of images</p> Signup and view all the answers

<p>To validate one’s understanding of the material. (C)</p> Signup and view all the answers

<p>False (B)</p> Signup and view all the answers

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

<p>Thermography (D)</p> Signup and view all the answers

<p>True (A)</p> Signup and view all the answers

<p>Understanding what images are and what they represent.</p> Signup and view all the answers

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

<p>Digital Image Processing 4th ed. = R. Gonzalez, R. Woods Image Processing and Computer Vision lecture slides = Prof. Joachim Weickert Biomedical Computation lecture slides = Jacob Levman Principles of Digital Image Processing: Fundamental Techniques = W. Burger, M. Burge</p> Signup and view all the answers

A course that focuses on manipulating and extracting useful information from digital images using computational methods.

Information gathered from visual input that influences how we think, communicate, and make decisions.

Defects or imperfections in an image that can hinder its quality or clarity.

Steps or procedures applied to images to enhance them, remove imperfections, extract patterns, or obtain specific information.

Extracting meaningful insights or understanding from images.

Python with additional libraries like scikit-image and numpy. This allows for image processing and manipulation.

The purpose for performing image processing, such as photo enhancement, medical imaging, or forensics.

A document that provides clear instructions on how to reproduce research results or run code, ensuring reproducibility and transparency.

Submission of work that is not entirely your own, including copying from another source or collaborating with another student on an assignment.

It means being aware of and adhering to the rules regarding academic integrity. This involves understanding what constitutes plagiarism, cheating, and other forms of academic dishonesty.

The UPM email account is the primary communication channel for course updates, announcements, and official communication between the instructor and students. Students are expected to check their UPM email regularly.

Students are expected to be present at all scheduled classes. Attendance is tracked, and excessive absences will be reported to the appropriate authorities.

Students are encouraged to discuss high-level concepts with peers to facilitate learning, but working on assignments together is strictly prohibited.

Students are expected to complete all assignments independently. Any form of collaboration on assignments that results in similar work will be deemed cheating.

Any instances of academic misconduct will be dealt with seriously. Penalties may include a failing grade for the assignment or course, or even expulsion from the university.

The syllabus contains important information related to the course. Students are responsible for reading and understanding the entire syllabus.

Converting real-world images into a digital format that computers can understand and process. This involves representing image data as a series of numbers, typically representing pixel values.

Basic manipulations performed on images, such as resizing, rotating, or flipping the image. These transformations are often used in image processing for preparing images for further processing or for visual effects.

A method of representing an image in terms of its frequency components, breaking down the image into different frequencies that contribute to its overall structure. This is often used for image analysis and processing.

Techniques that aim to improve the quality or enhance the visual appearance of an image. They can increase contrast, sharpen edges, or reduce noise.

A type of image processing that analyzes and modifies an image based on the frequencies of its components.

Techniques used to restore images that have been degraded due to noise, blurring, or other imperfections. These methods attempt to recover the original image by removing or reducing the distortion.

A technique that considers color properties of an image, such as hue, saturation, and brightness.

Techniques that reduce the size of an image file while attempting to maintain its important visual information. This is useful for efficient storage and transmission of images.

A field of study and practice that deals with manipulating and analyzing digital images. It encompasses tasks like image enhancement, restoration, segmentation, and analysis.

DIP processes that focus on basic operations like brightness, contrast, and noise reduction.

DIP processes that involve extracting features and identifying patterns in images, such as edges, shapes, and textures.

DIP processes that involve using high-level knowledge and reasoning to understand and interpret images, such as scene recognition and object classification.

A branch of computer science that deals with enabling computers to 'see' and interpret images, often involving tasks like object detection, image recognition, and scene understanding.

A software application designed for professionals in the creative industries to edit and manipulate digital images.

The process of questioning your understanding and actively seeking clarification.

The act of communicating your confusion or uncertainty to your instructor or peers.

An image is a grid or matrix of intensity values, often represented by a 2D array of numbers. Each number in the array represents the brightness or color of a pixel at a specific location in the image.

A pixel is the smallest unit of an image, a single point on the image that can be assigned a color or brightness value.

In digital images, each pixel is assigned a numerical value representing its intensity. This value is usually an integer ranging from 0 to 255, where 0 represents black and 255 represents white. This range of numbers forms a grayscale scale for representing different colors.

An image can be visualized as a 2D array of pixels, where each pixel corresponds to a unique location on the image. Each location has an associated intensity value that determines the color or brightness at that point.

A 3D view of an image helps conceptualize the image as a layered structure, where each layer contains the intensity values for a specific color channel. For instance, in a color image, you'd have layers for red, green, and blue channels.

Thermography captures heat emitted by objects, allowing for temperature-based imaging. It can be used to detect abnormalities in the body, like the presence of tumors, by detecting temperature variations compared to surrounding areas.

Analyzing images to identify patterns or objects within the image, enabling applications like facial recognition, object identification, and scene understanding.

Visual Computing involves using computers to process, analyze, and understand visual information, spanning applications like image recognition, computer vision, and graphics.