problem_session.pdf - Chapter 1 CSE 4227 Digital Image...

Info icon This preview shows pages 1–5. Sign up to view the full content.

View Full Document Right Arrow Icon
1 CSE 4227: Digital Image Processing Dr S Rahman Professor, CSE, AUST Problem Session CSE | AUST Fall 2016 Chapter 1 1. Define and discuss how digital image processing, computer imaging, image analysis, computer vision applications, and human vision applications are related. Ans. Digital image processing is also referred to as computer imaging and can be defined as the acquisition and processing of visual information by computer. It can be divided into application areas of computer vision and human vision; where in computer vision applications the end user is a computer and in human vision applications the end user is a human. Image analysis ties these two primary application areas together, and can be defined as the examination of image data to solve a computer imaging problem. A computer vision system can be thought of as a deployed image analysis system. To develop human vision applications requires extensive use of image analysis and its methods. 2
Image of page 1

Info iconThis preview has intentionally blurred sections. Sign up to view the full version.

View Full Document Right Arrow Icon
2 Chapter 1 2. Discuss two computer vision applications. Ans. In general, a computer vision system has an imaging device, such as a camera, and a computer running analysis software to perform a desired task. Such as: A system to inspect parts on an assembly line. A system to aid in the diagnosis of cancer via MRI images. A system to automatically navigate a vehicle across Martian terrain. A system to inspect welds in an automotive assembly factory Chapter 1 3. List and describe the tools used in image analysis. Ans. The image analysis process requires the use of tools such as image segmentation, image transforms, feature extraction and pattern classification. Image segmentation is often one of the first steps in finding higher level objects from the raw image data. Feature extraction is the process of acquiring higher level image information, such as shape or color information, and may require the use of image transforms to find spatial frequency information. Pattern classification is the act of taking this higher level information and identifying objects within the image.
Image of page 2
3 Chapter 1 4. What are the major topics in the field of image processing for human vision applications? Discuss two applications. Ans. The major topics within the field of image processing include image restoration, image enhancement, and image compression. IP applications: restore old, degraded photographs; such as restore satellite images distorted by mechanical jitter on a spacecraft; sharpen an image to bring out details; compressing images in a way so they still look good; for special effect sin movies, etc Chapter 1 5. Suppose we need to develop a new image compression algorithm. Discuss the factors that must be considered. Ans. These questions will need to be considered: How much compression do we need? What quality of image do we need? How will we measure that quality? What visual information is important for this application? Do we need to be able to recreate the image exactly, or will an approximation do?
Image of page 3

Info iconThis preview has intentionally blurred sections. Sign up to view the full version.

View Full Document Right Arrow Icon
4 Chapter 1 6. What is the difference between image enhancement and image restoration?
Image of page 4
Image of page 5
This is the end of the preview. Sign up to access the rest of the document.

{[ snackBarMessage ]}

What students are saying

  • Left Quote Icon

    As a current student on this bumpy collegiate pathway, I stumbled upon Course Hero, where I can find study resources for nearly all my courses, get online help from tutors 24/7, and even share my old projects, papers, and lecture notes with other students.

    Student Picture

    Kiran Temple University Fox School of Business ‘17, Course Hero Intern

  • Left Quote Icon

    I cannot even describe how much Course Hero helped me this summer. It’s truly become something I can always rely on and help me. In the end, I was not only able to survive summer classes, but I was able to thrive thanks to Course Hero.

    Student Picture

    Dana University of Pennsylvania ‘17, Course Hero Intern

  • Left Quote Icon

    The ability to access any university’s resources through Course Hero proved invaluable in my case. I was behind on Tulane coursework and actually used UCLA’s materials to help me move forward and get everything together on time.

    Student Picture

    Jill Tulane University ‘16, Course Hero Intern