| dc.identifier.citation | [1] http://www.wordiq.com/definition /Morphological_image_processing [2] yzgrafik.ege.edu.tr/~aybars/ip/ Morphological%20Operations.ppt [3] Chris Solomon and Toby Breckon , Fundamentals of Digital Image Processing, Wiley-blackwell Press. [4] http://www.cs.auckland.ac.nz/ courses/compsci773s1c/lectures/ImagePro cessing-html/topic4.htm [5] Lixu Gu, J., Morphological segmentation for Image Processing and visualization, Robarts Research Institute London. [6] Thomas Moeslund, Morphology Lecture on the Image, Computer Vision and Media Technology Lab. Aalborg University. [7] Luc Vincent, June 1992, Morphological Grayscale Reconstruction: Definition, Efficient Algorithm and Application in Image Analysis, Proc. IEEE on Comp. Vision and Pattern Recog pp 633-635. [8] Marian M. Choy and Jesse S. Jin, Morphological image analysis of leftventricular 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, April 2004, Morphological image sequence processing, Journal Computing and Visualization in Science Volume 6 Issue 4. [10] L. Vincent, April 1993, Morphological grayscale reconstruction in image analysis: applications and efficient algorithms, IEEE Xplore pp 176-201. | en_US |
| dc.description.abstract | Morphological Image Processing is an important tool in digital image processing based on
human intuition and perception. The morphology is based on the geometry, which emphasizes
the geometry of the image. The 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 Rontgen or scanning of the resulting images do not have the accuracy of
the expected image quality. This is because of factors of body movement or instrument (not
focusing) so that the resulting image is blurred and distorted. One method is to enhance this
image by using morphology method. With operations of 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 this study
optimal results are obtained for the distorted image with SNR of 19.891 dB, reduction bits of
2.206, and Gain of 13.27 dB. | en_US |
