Description
Brain Tumor Analysis Using Cuckoo Search Optimization
A combination of airborne and satellite-based remote sensing is currently used for operational oil-spill monitoring worldwide. Spaceborne satellite-based synthetic aperture radar (SAR) images provide an overview of large ocean areas, and surveillance aircraft can be directed to check possible oil-spill locations to verify the spill and catch the polluter. Oil-spill detection is most effectively performed on a large scale using SAR images due to its all-weather capabilities (given wind speeds in the range of 2? 14 m/s) and good coverage.? In this paper by using a neural network the oil spill regions have been extracted in the radar image. Brain Tumor Analysis Using Cuckoo Search Optimization – Matlab
Brain Tumor Analysis Using Cuckoo Search Optimization
Existing Method
- Principal Component Analysis
- Local binary pattern and shape features
- KNN and FNN classifier
Drawbacks of Existing method
- High Computational load and poor discriminatory power.
- LBP doesn’t differentiate the local texture region.
- FNN is slow training for a large feature set.
- Less accuracy in classification
Proposed Method
- DRLBP and GLCM
- Neural Network classifier
Methodologies
- Color Space Conversion
- GLCM Features Extraction
- DRLBP (Discriminative Robust Local Binary Pattern)
- NN Training and Classification
- Fuzzy c-means clustering
Advantages
- DRLBP has better discriminatory power
- NN is fast and better compatible in classification.
- Low computational complexity
Application
- Surveillance aircraft
- Oil-spill monitoring
Software Requirement
- Matlab2014a and above versions
REFERENCES:
[1] R. Mahr and C. R. Chase, BOil spill detection technology for early warning spill prevention,[ in Proc. MTS/IEEE OCEANS Conf., 2009, pp. 1? 8.
[2] A. Dierks, V. L. Asper, R. Highsmith, M. Woolsey, S. Lohrenz, K. McLetchie, A. Gossett, M. Lowe, D. Joung, L. McKay, S. Joye, and A. Teske, BNIUSTVDeepwater horizon oil spill response cruise,[ in Proc. OCEANS, 2010, DOI: 10.1109/OCEANS.2010. 5664443
[3 D. Kim, W. Moon, and Y.-S. Kim, application of TerraSAR-X data for emergent oil-spill monitoring,[ IEEE Trans. Geosci. Remote Sens., vol. 48, no. 2, pp. 852? 863, Feb. 2010.
[4] ] I. Keramitsoglou, C. Cartalis, and C. Kiranoudis, automatic identification of oil spills on satellite images,[ Environ. Model. Softw., vol. 21, no. 5, pp. 640? 652, 2006
[5] ] D. Casciello, T. Lacavat, N. Pergolat, and V. Tramutoli, BRobust satellite techniques (RST) for oil spill detection and monitoring,[ in Proc. Int. Workshop Anal. Multi-Temporal Remote Sens. Images, 2007, DOI: 10.1109/ MULTITEMP.2007.4293040
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