Image edge detection system / Azimah Razali

Azimah, Razali (2003) Image edge detection system / Azimah Razali. Undergraduates thesis, University of Malaya.

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    Image edge detection is not a new thing in image processing. It has been applied so many years ago as one of the technique or method to produce a variation of image display either for medical, research or art. For example in medical field, they used this method for X-Ray. This thesis describes edge detection in details including the edge definition, the types of edge, detection methods, the problems with edge, the advantages and disadvantages and the most important is how to detect edge in digital image, either two-dimensional or three-dimensional images. In this system, two main methods that are implemented are Laplacian and Gaussian. For the Gaussian method, it divides to two parts, the first one for one dimensional image called One Dimensional Gaussian and the other one is for two dimensional image called Two Dimensional Gaussian. Beside these three methods, there are three other operators that are also used in image detection process. They are Robert operator, Sobel operator and Prewitt operator. But the user does not need to use all of these operators, they just need to chose any one of them to be applied on their scanned images. Though all of these operators are functioning in three different ways, the result is still the same. In other word, this thesis explores the methods or techniques of image edge detection in detail until software that can detect edge was developed and available to use by users.

    Item Type: Thesis ( Undergraduates)
    Additional Information: Academic Exercise (Bachelor’s Degree) – Faculty of Computer Science & Information Technology, University of Malaya, 2002/2003.
    Uncontrolled Keywords: Image edge detection system; One dimensional image; Digital image; Two dimensional image; X-Ray
    Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
    Divisions: Faculty of Computer Science & Information Technology
    Depositing User: Mr Mohd Safri Tahir
    Date Deposited: 24 Sep 2019 01:12
    Last Modified: 20 Feb 2020 05:38

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