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Physical Sciences and Mathematics Commons™
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Articles 1 - 4 of 4
Full-Text Articles in Physical Sciences and Mathematics
Pixel- Versus Object-Based Classification Of Forest And Agricultural Areas From Multiresolution Satellite Images, Di̇jle Boyaci, Mustafa Erdoğan, Ferruh Yildiz
Pixel- Versus Object-Based Classification Of Forest And Agricultural Areas From Multiresolution Satellite Images, Di̇jle Boyaci, Mustafa Erdoğan, Ferruh Yildiz
Turkish Journal of Electrical Engineering and Computer Sciences
Managing of natural resources including agriculture and forestry is a very important subject for governments and decision makers. Up-to-date, accurate, and timely geospatial information about natural resources is needed in the management process. Remote sensing technology plays a significant role in the production of this geospatial information. Compared to terrestrial work, the analysis of larger areas with remote sensing techniques can be done on a shorter timescale and at lower cost. Image classification in remote sensing is one of the most popular methods used for the detection of forest and agricultural areas. However, the accuracy of classification changes according to …
Universal And Stable Medical Image Generation For Tissue Segmentation (The Unistable Method), Ihab Elaff, Ali El-Kemany, Mohammed Kholif
Universal And Stable Medical Image Generation For Tissue Segmentation (The Unistable Method), Ihab Elaff, Ali El-Kemany, Mohammed Kholif
Turkish Journal of Electrical Engineering and Computer Sciences
Segmentation of medical images has been one of the most important research areas because of its impact in modeling and diagnosing the structure and the functions of various organs. The lack of unique solution for the segmentation problem of medical images is caused by the wide range of selections among different medical imaging modalities and clustering methods where each setting has its own estimates for solving this problem. The unistable method is a novel method that generates enhanced images with high contrast, which can reduce boundary overlap between different tissues. This is accomplished by fusion of different clustering maps, which …
Multiphase Segmentation Based On New Signed Pressure Force Functions And One Level Set Function, Haider Ali, Noor Badshah, Ke Chen, Gulzar Ali Khan, Nosheen Zikria
Multiphase Segmentation Based On New Signed Pressure Force Functions And One Level Set Function, Haider Ali, Noor Badshah, Ke Chen, Gulzar Ali Khan, Nosheen Zikria
Turkish Journal of Electrical Engineering and Computer Sciences
In this paper we propose a new model to detect multiple objects of various intensities in images having maximum, minimum, or middle-intensity background by evolving only one level set function. In this model, a new signed pressure force function based on novel generalized averages is used for segmentation of images with maximum or minimum intensity background. For images with middle-intensity backgrounds, which are indeed challenging for 2-phase models, we propose a new product generalized signed pressure force function. Finally, to give experimental and qualitative evidence, our model is tested on both synthetic and real images with the Jaccard similarity index. …
A New Segmentation Method Of Cerebral Mri Images Based On The Fuzzy C-Means Algorithm, Mohamed Zaki Abderrezak, Mouatez Billah Chibane, Karim Mansour
A New Segmentation Method Of Cerebral Mri Images Based On The Fuzzy C-Means Algorithm, Mohamed Zaki Abderrezak, Mouatez Billah Chibane, Karim Mansour
Turkish Journal of Electrical Engineering and Computer Sciences
The aim of this work is to present a new method for cerebral MRI image segmentation based on modification of the fuzzy c-means (FCM) algorithm. We used local and nonlocal information distance in the initial function of the robust FCM model. The obtained results of the classification of MRI images showed the effectiveness of the suggested model. Calculation of the similarity index confirms that our method is well adapted to MRI images even in the presence of noise.