| dc.identifier.citation | [1] http://www.wordiq.com/definition/Morphological_image_processing [2] yzgrafik.ege.edu.tr/~aybars/ip/.../Morphological%20Operations.ppt [3] Fundamentals of Digital Image Processing, Chris Solomon and Toby Breckon, Wiley-blackwell Press. [4] http://www.cs.auckland.ac.nz/courses/compsci773s1c/lectures/ ImageProcessing-html/topic4.htm [5] Morphological segmentation for Image Processing and visualization, Lixu Gu, J. Robarts Research Institute London. [6] Morphology Lecture on the Image, Thomas Moeslund, Computer Vision and Media Technology Lab. Aalborg University. [7] Luc Vincent, Morphological Grayscale Reconstruction: Definition, Efficient Algorithm and Application in Image Analysis, Proc. IEEE on Comp. Vision and Pattern Recog pp 633-635 June 1992. [8] Marian M. Choy and Jesse S. Jin, Morphological image analysis of left-ventricular endocardial borders in 2D echocardiograms, School of Computer Science and Engineering University of New Sauth Wales Sydney Australis. [9] Karol Mikula, Tobias Preusser, and Martin Rumpf, Morphological image sequence processing, Journal Computing and Visualization in Science Volume 6 Issue 4, April 2004. [10] L. Vincent, Morphological grayscale reconstruction in image analysis: applications and efficient algorithms, IEEE Xplore April 1993 pp 176-201. | en_US |
| dc.description.abstract | Image Processing morphology is an important tool in digital image
processing based on human intuition and perception. Morphology based on
the geometry, which emphasizes the geometry of the image. Morphology of
the process is mainly used to remove the imperfections that exist in the form
of an image. No exception in the field of medicine/medical, often obtained
results rontgent or scanning the resulting images do not have the accuracy of the
expected image quality. This is because factors of body movement or instrument
(not focusing) so that the resulting image blur and distorted. One method is to
enhance this image by using morphology method. With operations erosion and
dilation as well as a combination of both in the process of opening and closing,
the morphology of high level/complex projects could be implemented. The
key to success lies in the selection process of the morphology of mathematical
operations and the choice of structured elements. Even the selection of filters and
methods of transformation in this process is often not used. In a study obtained
optimal results for the distorted image with SNR 19.891 dB, reduction bits 2.206,
and Gain 13.27 dB. | en_US |
