IJPAM: Volume 67, No. 3 (2011)
Virginia Commonwealth University Qatar
P.O. Box 8095, Doha, QATAR
e-mail: jschmeelk@qatar.vcu.edu
Abstract.Image edge detection is an integral component of image processing to enhance
the clarity of edges and the type of edges. Issues regarding edge techniques
were introduced in my 2008 paper on transforms, filters, and edge
detectors, see [15]. The current paper provides a deeper analysis regarding
image edge detection using matrices; partial derivatives; convolutions; and
the software, MATLAB 7.9.0, and MATLAB Image Processing Toolbox 6.4.
Edge detection has applications in all areas of research, including medical
research, see [6], [13]. For example, a patient can be diagnosed as
having prostate cancer by studying the edges of the cells (see Figure 1).
One can study a magnetic resonance (MR) brain image to indicate the edge
functional, as illustrated in Russ, see [13] and Figure 2. Additionally, a
patient can be diagnosed with an aneurysm by studying an angiogram (see
Figure 3). The physician can study the angiogram, an image of the view of
the problematic blood vessels, and determine the diameter of the increased
size. The previous paper (see [15]) studied letters using vertical, horizontal,
and Sobel transforms. This paper will study images to include the letter
and two images, those of Cameraman and Rice, included in the library of the Image
Processing Toolbox 6.4. We then compare the techniques implemented in the
previous paper (see [15]) and the images, letter
Cameraman, and Rice, using vertical,
horizontal, Sobel, and Canny transforms implementing the software, MATLAB 7.9.0, and Image Processing Toolbox 6.4.
Received: January 11, 2011
Source: International Journal of Pure and Applied Mathematics
ISSN: 1311-8080
Year: 2011
Volume: 67
Issue: 3