ROBUST SEGMENTATION OF DEFORM OBJECTS USING MORPHOLOGICAL SCALE SPACE
Journal: International Journal of Computer Engineering and Technology (IJCET) (Vol.8, No. 4)Publication Date: 2017-08-30
Authors : HAYTHEM EL-MESSIRY;
Page : 138-145
Keywords : Segmentation; deform; morphological scale space; robust.;
Abstract
The paper presents a method towards a robust segmentation that can be used in sequential images. The proposed method combines low-high level methods, which asserts prior information about local structure around control points along the deformable boundary. The method has ability to preserve multi resolution, and the localization of sharp-edges by taking the advantage of using the morphological scalespace by decomposing the image into a number of scales of different structure size. The method was tested on sequential of medical images 23 frames per heart cycle and compared to two other approaches. The estimated boundary converges correctly to the main contour with maximum distance error 5 pixels over all control points.
Other Latest Articles
- DECISIVE HIGH-UTILITY ITEM SET MINING - AN INNOVATIVE ALGORITHM FOR MINING THE HIGH UTILITY ITEMSETS
- IMPACT OF SOFTWARE TESTING METRICS ON SOFTWARE MEASUREMENT
- PRIVACY PRESERVING ASSOCIATION RULE MINING FROM HIGHLY SECURED OUTSOURCED DATABASES
- ARTIFICIAL-NOISE-AIDED MESSAGE AUTHENTICATION CODES WITH INFORMATION-THEORETIC SECURITY
- LINKING OF UNIQUE NATIONAL IDENTITY NUMBER WITH E-VOTING FOR SECURE TRANSPARENCY AND VERIFICATION
Last modified: 2017-12-23 18:32:17